ExtendSim popularity in higher institutions has experienced phenomenal growth as researchers have learned of ExtendSim's ease of use combined with its high level of accuracy. ExtendSim has become an indispensable component supporting essential phases of innovative research projects in universities worldwide.
In response to the growing popularity of using ExtendSim in research projects, we established the ExtendSim Academic Research Grant program. Under the Grant, Imagine That Inc. supports students who are obtaining an advanced degree (Masters Thesis, PhD, or PostDoc) by subsidizing the cost of a full Model Developer Edition of ExtendSim for use by the student during the term of their research project. In exchange, the student provides a description of the research and quarterly updates throughout the term of the project. At the end of the research, all findings (ie. paper, project, etc.) and the ExtendSim model formulated are passed on to Imagine That Inc. for publication on the ExtendSim web site.
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Current Academic Research Grants
These research projects have been awarded an ExtendSim Academic Research Grant and are currently in progress. To learn about past projects completed under the ExtendSim Academic Research Grant program, please see Academic Research Grants Fulfilled.
Bioenergy Supply Chain and Logistics
Vulnerability, Risk and Resilience Approaches for Bioenergy Supply Chain and Logistics
Devita McCullough-Amal
Virginia Polytechnic Institute and State University
Phd in Industrial Systems Engineering
Grant awarded: August 30, 2017
To be completed: December 31, 2018
Hypothesis.
If appropriate mitigation strategies are implemented, then increases in performance will be observed for select members of the supply chain.
Project description.
Bioenergy, in the form of lignocellulosic biomass, sugars and starches, offer significant potential to alleviate climate change by mitigating greenhouse gas emissions and reducing the dependence on fossil based energy sources. However, many questions remain regarding the performance of the bioenergy supply chain under various risks and disruptions, along with implications of potential mitigation strategies. This study seeks to address these questions and provide insight on the design of robust biomass supply chain systems.
Questions this research will answer.
- What are the implications of biomass supply disruptions on the performance of the supply chain?
- What mitigation strategies can improve the performance of the supply chain?
How research strategy will be designed to help answer these questions.
- Develop a modeling framework that quantifies the performance of the biomass supply chain.
- Evaluate the supply chain impacts that result from disruption in biomass supply.
- Determine the effectiveness risk mitigation strategies on the operational and financial stability of the biomass supply chain.
How ExtendSim will be used in this project.
ExtendSim will be used for the development of the discrete event simulation of the harvest and operational activities of the biomass supply chain.
What is unique about this project?
This work is unique in that we develop a holistic model of biomass supply chain, and quantify the performance of the supply chain using this developed model. As opposed to previous biomass models, this model intends to examine the supply chain at a higher resolution, and taking an integrated systems approach which accounts for external systems not previously considered such as market demand, rate of grower participation, etc.
Why the interest in the indicated subject?
To date, the uncertainty associated with various forms of biomass supply risks have been problematic for the bioenergy industry. There is great interest in devising solutions that can help to tackle these problems and advance the industry.
What impact will this research make to the existing current state of knowledge?
This research has enormous learning potential, particularly in the areas of upstream management of biomass supply risk, viable mitigation strategies, and holistic supply chain model development.
Publications.
Amal, D., A. Salado, and E. Webb. 2017. Modeling Biomass Supply Chain Disruptions in the US. ASABE Annual International Meeting, July 16-19, 2017 Spokane, Washington, USA
Amal, D., A. Salado, and E. Webb. 2017. Biomass Supply Chain Risk: A Systematic Review. ASABE Annual International Meeting, July 16-19, 2017 Spokane, Washington, USA
McCullough, D., R.D. Grisso, and J.S. Cundiff. 2013. Discrete Event Simulation of Switchgrass Harvest Schedules. ASABE Paper and Presentation. St. Joseph, MI:ASABE
Grisso, R.D., D. McCullough, J.S. Cundiff, and J. Judd. 2013. Harvest schedule to fill storage for year-round delivery of grasses to biorefinery. Biomass & Bioenergy
Crowd Management During the Hajj
Hajj Crowd Analysis: Incidents and Solutions
Almoaid Owaidah
University of Western Australia
PhD in Computer Science
Grant awarded: July 21, 2019
To be completed: December 2021
Extended to: October 1, 2022
Project plan.
- Research Proposal submission
- Literature Review
- Analysing previous crowd incidents (objective 1 & 2)
- Designing Hajj crowd simulation model (objective 3 & 4)
- Building Hajj crowd simulation model (objective 3 & 4)
- Model verification (objective 3 & 4)
- Run the Hajj crowd simulation (objective 3 & 4)
- Model validation (objective 3 & 4)
- Hajj crowd simulation findings and results (objective 5)
- Thesis writing
Questions this research will answer.
- How to simulate Hajj events under different scenarios to save pilgrim’s time and lives?
- How to simulate Hajj events to propose new crowd management methods?
- How to simulate Hajj events to deliver appropriate responses to unexpected incidents?
- How to develop methods to analyse previous crowd incidents at Hajj events?
How research strategy will be designed to help answer these questions.
Individual/separate models for each of the events are currently underway. However, they cannot be integrated under the limitation of the student version. The models are designed for normal conditions and validated against the 2018 statistics for Hajj (durations of various rituals, number of pilgrims by country of origin, service levels, bottlenecks/capacity limitations). However, as part of the sensitivity analysis, changes in allocations, characteristics and behaviours of the pilgrims, operation of various facilities (train, buses) etc. will be tested.
How ExtendSim will be used in this project.
Extendsim is the main software for modelling and simulation Hajj event.
What is unique about this project?
Most of the work undertaken before examined in great detail interaction between pilgrims during Tawaf (at the Grand Mosque) and Stoning the Devil (at the Aljamarat Bridge), which represent the most crowded events of the Hajj. Given the confined space and weather conditions, often incidents occur, with tragic consequences. Instead of using an agent-based model to simulate interactions between individuals, I opted for modelling the whole sequence of Hajj at the level of a guided group (up to 250 individuals with a local guide trained specifically for the event). The innovation is in integrating the events and incorporating travel between sites, which has not been undertaken before.
Why the interest in the indicated subject?
The integration and link all Hajj models as a wholistic model.
What impact will this research make to the existing current state of knowledge?
The research will have implications for both academia and practice: understanding the most challenging aspects of Hajj and whether/how scheduling the arrivals of the pilgrims at various sites may alleviate crowding and improve the operation of the whole event provides insights on organising other mass gathering events. It is expected that transport may play a key role in improving the flow, but this has not been tested. On the managerial side, higher performance indicators mean a better experience for the pilgrims, ensuring safe events and without incidents. The results may assist planning of future events, understanding capacity limitations, providing training tips for the local guides on aspects that may cause issues during the event.
Research site.
Almoaid A. Owaidah on Google Scholar.
Publications.
A. Owaidah, D. Olaru, M. Bennamoun, F. Sohel and R. Nazim Khan, "Modelling Mass Crowd Using Discrete Event Simulation: A Case Study of Integrated Tawaf and Sayee Rituals during Hajj", in IEEE Access, doi: 10.1109/ACCESS.2021.3083265.
Updates.
October 4, 2021 - After I have published my work on crowd management at The Grand Mosque at Hajj event, I have been working on two things. First, transport management at Hajj event and how pilgrims are transported between three holy sites by buses, trains and pedestrian routes. Second, crowd management of pilgrims at Aljamarat Bridge. I have also developed scenarios in case of an emergency occurs and how pilgrims can be evacuated from the bridge.
The work of crowd management at Aljamarat bridge has been submitted to the MODSIM conference 2021, which will take place in Sydney 2021. The transport work will be presented and submitted in a journal. I am now validating the results of the models then will develop scenarios of these models.
May 25, 2021 - The first of 3 papers has been published at https://ieeexplore.ieee.org/document/9439797. Click here to see screenshots of the model in progress.
July 23, 2020 - As Hajj consists of rituals and pilgrims' movements, our primary objective is to model Hajj rituals by simulating millions of pilgrims and their movements between Hajj Holy sites using different modes of transport (Shuttle buses, Conventional buses, train and walking). As Hajj is done at certain days (5 days), we have built Hajj models to simulate the reality of Hajj event, to identify different factors that could affect the organization of the pilgrims (e.g. Level of Service, crowd density, crowds flow, potential hazards, duration of ritual activities, duration of transport etc...).
We have developed the first paper using ExtendSim pretesting Hajj days one and 2. in this paper; we have designed a ritual model (Tawaf and Sayee) and two movement models (transport from Makkah to Mina and from Mina to Arafat). In addition, Scenarios have been designed to study the different aspects of crowd behaviours, as mentioned previously.
Crowd Management • Holy Rawda of Prophet Mohammed Mosque
Marwa Saleh Sonbul
King Abdulaziz University
Masters in Information Systems
Grant awarded: February 24, 2020
To be completed: December 2020
Project description.
- Identify the current visiting features as quantitative parameters and features for the optimum visiting experience.
- Simulate the current situation of the visit, using specific parameters of Rawda constraints.
- Design different visiting patterns (path, crowd density, and visiting intervals) through simulating different scenarios to achieve optimum visiting experiences.
- Visualize three best scenarios that can help enhance the visiting experience to demonstrate the solution in a graphical fashion.
Questions this research will answer.
- How best the visiting experience can be improved under the given constraints to achieve optimum experience?
- What is the visiting pattern (path, crowd density, and visiting intervals) that can clearly enhance visiting experience?
- How can the chosen visiting pattern be visualized to demonstrate the features of an enhanced visiting experience?
How research strategy will be designed to help answer these questions.
Research will follow these steps:
- Background reading
- Literature review
- Data collection
- Implementation
- Results and discussions
- Recommendations and future work
How ExtendSim will be used in this project.
I will use it to simulate the current scenario of visiting Rawda, then extract the results. After that I will simulate different improved scenarios.
What is unique about this project?
There is a lack of managing the crowd for female visitors entering the Rawda; which may cause collisions and decrease their enjoyment of this spiritual experience.
Why the interest in the indicated subject?
I want to make good use of my opportunities as a citizen to solve a common problem in my country.
Publications.
Aljuhani, K., Sonbul, M., Althabiti, M., & Meccawy, M. (2018). Creating a Virtual Science Lab (VSL): the adoption of virtual labs in Saudi schools. Smart Learning Environments, 5(1), 16.
Digital Twin • Assembly Plant
Simulation AssemblyPontus Persson & Tim Snell
Luleå Tekniska Universitet
Masters in Mechanical Engineering
Grant awarded: February 21, 2020
To be completed: May 30, 2020
Hypothesis.
How can an assembly process be optimized by validation through a simulation model.
Project description.
The plan is to first build a digital twin of an assembly production. Once the digital twin is built and validated, different scenarios can be evaluated.
Questions this research will answer.
- What is the most optimal state of the buffer system?
- How can TTR and TBF of assembly stations be optimized and what are the affects?
How research strategy will be designed to help answer these questions.
Build a process map, build a conceptual model (already done), build a digital twin and gather process data, and lastly evaluate different scenarios.
How ExtendSim will be used in this project.
ExtendSim will be used to build the simulation model which is the essential part of this project.
What is unique about this project?
Stoppage times will be used to define TTR and TBF which will be essential for creating a valid model. Therefore, the ExtendSim Reliability library will be an essential part in this project.
Why the interest in the indicated subject?
My master thesis partner and I have worked with ExtendSim in previous courses, but have never used the Reliability library.
What impact will this research make to the existing current state of knowledge?
The company we are working towards wants to use the simulation model for implementation and evaluation of further production changes.
Updates.
March 17, 2020 - We have not yet started building our model. We are still trying to figure out how we are going to include the reliability model in our DE model. To date, we have been working on:
- Pre study (previous DES projects and methods for similar projects)
- Process mapping and status analysis
- Gathering of process stop data (TTR and TBF)
- Building conceptual models
- Generate distributions using Excel and Stat::Fit
- Looking into the Reliability module (We are having some issues with this and have been in contact with Imagine That Inc. for assistance.)
Digital Twin • Critical Services Provider
Model-Based Systems Engineering
Xueping Li plus a team of Grad Students in the Department of Industrial & Systems Engineering
University of Tennessee, Knoxville
Grant awarded: May 10, 2022
To be completed: December 31, 2022
Hypothesis.
We propose the concept of using simulation as a soft digital twin to address complex decision-making processes in the age of digital transformation. The central hypothesis is that a well-developed simulation model is able to provide insights into critical business processes, conduct scenario analysis, and ultimately optimize the overall system performance.
Project description.
We adopt a multi-phased research plan for an undisclosed organization that provides critical systems.
Phase 1: Identify one area of interest (e.g., the maintenance organization) for detailed systems analysis. Identify model elements such as: variables, stocks, flows, and inter-relationships. Develop conceptual model structures. Establish functional requirements (e.g., real-time data acquisition, intelligent adaptation (machine learning), what-if scenarios, optimization capability, etc.) Define and establish the data sources, systems process mapping (including initial causal loop diagrams). Identify optimal modeling approaches (in consideration of multi-method modeling). Develop final causal flow diagrams, interfaces, and modeling elements for other appropriate methods.
Phase 2: Develop prototype model(s) for designated systems. Efforts include defining desired functionality, design and operational requirements, operating parameters, data resource needs, visualization, user interface, portability and access, system boundaries, and programing dictionaries (data, variables, parameters, links, interfaces, machine intelligence functionality etc.). Initial models will be constructed for proof-of-concept demonstration and preliminary V&V.
Phase 3: Complete design of the systems model, finalize verification and validation, complete UI and data visualization, complete documentation, and validate systems interface operability.
Questions this research will answer.
- RQ1: Will the soft digital twin, i.e., the simulation model, be able to produce results (e.g., throughput, overall job cycle time, resource utilization, etc.) that is comparable to historical system performance through a data-driven approach?
- RQ2: Will the soft digital twin help conduct what-if analysis with high confidence?
- RQ3: Will the soft digital twin help with system optimization under given certain operational constraints?
How research strategy will be designed to help answer these questions.
Please refer to the aforementioned multi-phase research plan.
How ExtendSim will be used in this project.
We plan to use ExtendSim to build the simulation model for the identified system (i.e., the maintenance system).
What is unique about this project?
The undisclosed organization that we work with provides critical services that demand high availability and any downtime will lead to exorbitant high costs.
Why the interest in the indicated subject?
Modeling and simulation have been one of my major research areas. The potential use of simulation as a digital twin is of particular interest to me.
What impact will this research make to the existing current state of knowledge?
We will have graduate research students working on the project. We intend to publish our research findings that will be disseminated widely.
Publications.
I have published 140+ peer-review journal and conference papers. Below are a few recent publications.
Zeyu Liu, Anahita Khojandi, Xueping Li, Akram Mohammed, Robert Davis, and Rishikesan Kamaleswarn (2022). A Machine Learning-Enabled Partially Observable Markov Decision Process Framework for Early Sepsis Prediction. INFORMS Journal on Computing.
Rodney Kizito, Zeyu Liu, Xueping Li, Kai Sun (2022). Multi-stage Stochastic Optimization Of Islanded Utility-microgrids After Natural Disasters. Operations Research Perspectives, No. 100235.
Chien-fei Chen, et al. (2022). Extreme Events, Energy Security and Equality through Micro and Macro Levels: Concepts, Challenges and Methods. Energy Research & Social Science, Vol. 85, No. 102401.
Yulin Sun, Cong Guo and Xueping Li (2022). An Order-Splitting Model for Supplier Selection and Order Allocation in a Multi-echelon Supply Chain. Computers and Operations Research, Vol. 137, No. 105515.
Rodney Kizito, Zeyu Liu, Xueping Li and Kai Sun (2021). Stochastic Optimization of Distributed Generator Location and Sizing in an Islanded Utility Microgrid During a Large-Scale Grid Disturbance. Sustainable Energy, Grids and Networks, Vol. 27, No. 100516.
Kaike Zhang, Xueping Li, and Mingzhou Jin (2021). Efficient solution methods for a general r-interdiction median problem with fortification. INFORMS Journal on Computing.
Rodney Kizito, Phillip Scruggs, Xueping Li, Michael DeVinney, Joseph Jansen, and Reid Kress (2021). Long Short-Term Memory Networks for Facility Infrastructure Failure and Remaining Useful Life Prediction. IEEE Access, Vol. 9, pp. 67585 - 67594. (doi.org/10.1109/ACCESS.2021.3077192).
Zeyu Liu, Anahita Khojandi, Akram Mohammed, Xueping Li, Lokesh K. Chinthala, Robert L. Davis, Rishikesan Kamaleswaran (2021). HeMA: A hierarchically enriched machine learning approach for managing false alarms in real time: A sepsis prediction case study. Computers in Biology and Medicine, Vol. 2021, No. 104255.
Chuang Liu, Huaping Chen, Xueping Li, Zeyu Liu (2021). A Scheduling Decision Support Model For Minimizing The Number Of Drones With Dynamic Package Arrivals And Personalized Deadlines. Expert Systems With Applications, Vol. 167, No. 114157.
Thomas Berg, Xueping Li, Tami Wyatt, Rupy Sawhney (2021). Agent-Based Modeling Simulation of Nurse Medication Administration Errors. Computers, and Nursing Informatics, Vol. 39, No. 4, pp. 187-197.
Yongzhen Li, Xueping Li, Jia Shu, Miao Song, Kaike Zhang (2021). A General Model and Efficient Algorithms for Reliable Facility Location Problem under Uncertain Disruptions. INFORMS Journal on Computing.
Updates.
Coming soon!
Feedstock Supply Chain for Biofuels and Biochemicals
Integrated Simulation Modeling for Supply Chain Impacts of Genetic Improvements in Switchgrass
Haley Stauffer
Pennsylvania State University
Masters of Science in Agricultural and Biological Engineering
Grant awarded: October 29, 2019
To be completed: June 2021
Hypothesis.
New high-yielding, more sustainable varieties of switchgrass developed in the Center for Bioenergy Innovation (CBI) will significantly impact the feedstock supply chain for biofuels and biochemicals.
Project description.
Acquire statistical data on switchgrass yield with respect to specific phenotypes. Determine the current and potential yield of switchgrass in the US, using a specific area for a case study. Following this case study evaluation, I will assess the supply chain parameters (availability of land, distance to a biorefinery, trucking/equipment needed) based on scale and pricing.
Questions this research will answer.
- What switchgrass phenotypes are the most robust (optimal in yield, yield stability)? Need to get data from Feedstock Sustainability Team and John Field, especially Water Use Efficiency (WUE) and Nitrogen Use Efficiency (NUE). Those can be modeled in DayCent.
- What is the yield capacity for switchgrass (and biofuel from switchgrass) in the U.S.? Need to get data from BillionTon2016, perhaps modified by John Field.
- What are the risks and uncertainties within the switchgrass supply chain?
- How do different switchgrass phenotypes affect the risk and uncertainties in the supply chain?
How research strategy will be designed to help answer these questions.
My research strategy will involve utilizing the existing framework for supply chain modeling of poplar conducted by Oak Ridge National Laboratory (ORNL) and implementing the mass and energy metrics with respect to switchgrass. I will be working closely with Erin Webb at ORNL to specify particular research questions and gaps in understanding.
How ExtendSim will be used in this project.
I intend to gather mass and energy inputs for the ExtendSim model to determine the cost points in which a certain switchgrass phenotype will prove more advantageous environmentally (yield, yield stability, drought resistance) and economically.
What is unique about this project?
This specific project is unique because it analyzes the logistical advantages of improved phenotypes of switchgrass, focusing on crop establishment, harvest, storage, and transport to a bio-refinery. The capital, operating management costs pertaining to novel planting, harvesting, storage, and transportation logistics strategies are major deterrents to adoption of bioenergy production from switchgrass. The risks and uncertainties of switchgrass supply chains are largely undocumented. Understanding these uncertainties is crucial for successful adoption and implementation of switchgrass as an energy crop across the U.S.
Why the interest in the indicated subject?
I am interested in this topic as the logistical framework, such as cost, storage, equipment, or transportation factors, are key barriers to bioenergy adoption. Switchgrass is an important crop to North America for biofuel production as it is a non-food crop, requires fewer inputs than annual crops, can be grown on marginal land, and have enhanced drought tolerance due to their deep root structures (Langhotlz et al., 2014). It is important to learn about optimal phenotypes when accounting for risk and uncertainty in a crop's supply chain. Modeling for supply chain impacts from these different switchgrass phenotypes will provide key information for logistical gaps in commercial scale production.
What impact will this research make to the existing current state of knowledge?
ORNL will be utilizing this data to further their efforts in industrial scale research of bioenergy production from switchgrass. My thesis will provide an academic addition to the existing literature to better improve further knowledge of switchgrass supply chain needs and management.
Updates.
July 29, 2020 -- Ms. Stauffer was awarded first place in the poster competition at the Northeast Agricultural and Biological Engineering Conference (NABEC) for her work on this project.
July 27, 2020 -- I have been working on finalizing the production design structure by incorporating selected equipment at different stages along with their presumed quantity for the regional field case studies (Tennessee, Pennsylvania, and Iowa). I am incorporating the costs for this equipment as well as energy usage in addition to sorting through the supply shortage or supply surplus scenarios as they relate to costs. We are now sorting through uncertainty decision making and adjusting the most sensitive parameters for yield and yield stability within the model.
I would say I have made 20% progress on the ExtendSim model. Coordination with Robin Clark and Dr. Erin Webb at Oak Ridge National Laboratory have proved paramount in this project. I have weekly meetings with both of them as well as with my advisor, Dr. Tom Richard, and Dr. John Field at Colorado State University who is helping with the connection between the DayCent model for switchgrass, which is very soil and nutrient based, to ExtendSim's supply chain model.
Healthcare • Policy Setting for Operating Room Management
Surgery cancellation: causes, hospital-related strategies
Mona Koushan
Otago University
PhD in Management
Grant awarded: June 5, 2019
To be completed: May 31, 2021 & January 2022
Updated completion date: December 2022
Project description.
ExtendSim will be used to set a policy for OR management that balances the rate of surgery cancellation with hospital utilization taking into account the relationship and inter-relationship of different circumstances (e.g., scheduling policies, case mix, and hospital size) that affect policies.
Questions this research will answer.
- Which policy will be suitable for the hospital according to the circumstances?
- How does a manager set a policy that balances the rate of surgery cancellation and hospital utilization accounting for the circumstances they face?
How research strategy will be designed to help answer these questions.
To answer these questions, a discrete-event simulation will be used to investigate these relationships so Ms. Kaushan can develop a model/framework that will help the hospital manager to determine the most applicable policy considering the hospital’s circumstances.
How ExtendSim will be used in this project.
ExtendSim will be used to set a policy for OR management that balances the rate of surgery cancellation with hospital utilization taking into account the relationship and inter-relationship of different circumstances (e.g., scheduling policies, case mix, and hospital size) that affect policies.
What is unique about this project?
In general, studies consider a single policy to manage operation room capacity (and treat the policy as ‘fixed’ or ‘given’), but there are few articles that compare these policies and find which one can be more efficient (Y. B. Ferrand et al., 2014; Van Riet & Demeulemeester, 2015). While Duma & Aringhieri (2019) used each policy, they didn’t consider how hospital circumstances and various factors (outlined by Van Riet and Demeulemeester (2015), such as:
- the available number of ORs
- the available beds in downstream (ICU & PICU)
- operation duration characteristics
- scheduling policy
- patient volume
- case mix
...can affect the managers’ decision for setting an appropriate policy.
Why the interest in the indicated subject?
Increasing demand for healthcare service with limited resources has led to hospitals paying more attention to the use of resources. Given that the hospitals are naturally faced with different kinds of variability and uncertainty (such as surgery duration, length of stay (LOS), recovery duration and emergency arrivals), the fully planned of resources without any time buffers will require some level of surgery cancellations that will affect patient satisfaction. There are various factors that cause surgical cancellations. So, it become a main issue for the hospital manager to set a policy that balances the rate of surgery cancellation and hospital resource utilization, accounting for the hospital’s circumstances.
What impact will this research make to the existing current state of knowledge?
Today’s increasing demand for surgery and limited hospital resources has led to more surgery cancellations and resource under-utilization. Thus, solving this problem helps to even the patient flow while reducing the surgery cancellation (hospital-related causes) and managing the OR’s buffers with resource utilization according to the inherent uncertainty.
Publications.
Jahani, N., Jabalameli, M.S., Koushan, M., Rezaei Vandchali, H., Wood, L.C., "Bio-objective model for sustainable biofuel supply chain network design under uncertainties", Bioresource Technology Report (Derived from an external research project). Contribution: Validated the methodology and statistical analysis, interpreted, and wrote the final version of the manuscript. (Under review 2022).
Koushan, M., Wood, L.C., Greatbanks R. "A Scenario-based robust optimisation approach for multi-objective, multi-stage operating room scheduling with time and demand uncertainties", European Journal of Operational Research. (Under review 2022).
Koushan, M., Wood, L.C., Greatbanks R. Evaluating Factors Associated with the Cancellation and Delay of Elective Surgical Procedures: A Systematic Review, International Journal for Quality in Health Care. 2021, 33(2).
Duong, L. N. K.; Wang, J. X.; Wood, L. C.; Reiners, T.; Koushan, M. The Value of Incremental Environmental Sustainability Innovation in the Construction Industry: An Event Study. Constr. Manag. Econ. 2021, 0 (0), 1–21.
Koushan, M. Wood, L.C., Greatbanks, R. "Cause of surgery cancellation: A systematic literature review", Health Policy (submitted February 2020).
Koushan, M., Jolai, F., Wood, L.C., Hybrid Differential Evolution-Data mining (HDEDM) Algorithm for uncertain dynamic CMS problem, 48th International Conference of Computer and Industrial engineering, Auckland, New Zealand, December 2018.
Azadeh, A., Sheikhalishahi, M., Koushan, M. An integrated fuzzy DEA–Fuzzy simulation approach for optimization of operator allocation with learning effects in multi products CMS. Applied Mathematical Modelling (2013) 9922-9933.
Rafiei, H., Rabbani, M., Koushan, M., Effect of Motivation & Learning Curve In Dynamic Cell Formation And The Worker Assignment Problem, International Journal of Engineering Sciences & Research Technology (2012) 481-497.
Koushan, M., Jolai, F., Wood, L.C., Hybrid Differential Evolution-Data mining
(HDEDM) Algorithm for uncertain dynamic CMS problem, 48th International Conference of Computer and Industrial engineering, Auckland, New Zealand, December 2018.
Yadegari, M., Koushan, M., Inventory control, pricing of perishable items, taking into account time-dependent effects of inflation, 3th International Conference on Industrial Engineering and Sustainable Management, Isfahan, Iran, December 2016. (It was named one of the seven top articles).
Updates.
I was granted my Ph.D. degree and the thesis is embargoed in the University library for further publication. After a discussion with my supervisor, I decided to add more analysis to make the paper ready for publishing in a leading journal.
The model is ready, only further analysis is required which might take up to the end of the year.
Small-sized hospital hybrid policyJanuary 24, 20212 - I am working on extracting articles from my thesis that require further analysis. I have submitted my PhD thesis at the end of December 2021, which the estimated time for oral examination would be in April 2022. After the oral examination, I need to apply examiners’ comments on my thesis. ExtendSim models are designed, but further analysis is required to present the output of the model. View screenshots of in-progress models here.
Extended Grant to September 2022 for Mona to improve the research.
September 21, 2021 - The models are designed for three policies separately and the experiments are designed. Now it is the time to run the model with different policies and scenarios. There are 90 different statuses that must be examined with these models. View screenshots of in-progress models here.
Extended Grant to January 2022 due to COVID related delays in data collection.
May 3, 2021 - Since this project is directly related to health bodies, my projects has delayed in data collection stage due to COVID-19, which has affected simulation study. Please extend the Grant through September 2021.
In this stage I am preparing input data for simulation model which are extracted from conducted surgery scheduling model with MATLAB. The ExtendSim model is almost designed and it is examined in the small-size of hospital. The model is going to be run with different scenarios and different size of hospitals. In this case some part of model might be changed.
July 27, 2020 - I am modeling my simulation model to check with a usual surgery scheduling how different policies can help hospitals to improve performance (less surgery cancellation and more resource utilization). I intend to check the model and different policies with comprehensive surgery scheduling modeling too. Comparing generated data from these two models, hospital managers can easily decide which policy works more efficiently given their hospital circumstances.
My model is almost complete. I just need to add some formulation to calculate rate of surgery cancellation rate and add inputs.
Implementing Industry 4.0 • Building a Simplified, Self-Adjusting Order Release Mechanism
Simplified, self-adjusting order release mechanism as an "easy-to-adapt" interim solution on the way to true industry 4.0 processes.
Nils Daniel Schloemp
Hochschule Zittau/Görlitz
Diploma in Engineering
Grant awarded: October 12, 2021
To be completed: March 15, 2022
Hypothesis.
Lean management is a subject which is omni-present in todays manufacturing world. It often makes a noticeable impact towards profitability, by cutting the capital committed for resources to a minimum, thus helping the company to keep its liquidity and reducing the cost of capital.
This approach however does not come without its own set of risk, made all too clear, when a single container ship disrupted the flow of raw materials, semi-finished products, and OEM goods between Asia and the EMEA region, with the effects still being dealt with to this date.
In addition, many deployed Lean management solutions nowadays are complex systems, which grew over time not only in scope, but also their difficulty to understand. This leads to a high barrier of transition for companies willing to switch to a truly fully automated Industry 4.0 production, as often time only a select few employees fully understand the dependencies and necessities of the deployed systems.
A key part of any production system in general, but lean-managed systems in particular however, the time of order release into production is of distinct interest. The more time passes between start of production and time of sale, the higher the amount of committed capital will be as a result.
Thus, many companies strive to keep this time as short as possible, especially, if the goods produced either require expensive components, are produced high-volume or both.
This thesis attempts to develop, simulate, and validate a generalized approach to determine the ideal time of order releases in a MTO manufacturing environment, with overall drastically reduced complexity and the ability to self-adjust to shifting demands (and thus, shifting production-bottlenecks) on a real-time basis. To reach this goal, it is planned to utilize ExtendSim to simulate and observe the impact of nested m-ConWIP systems with varying WIP levels, to determine not only the ideal WIP level, but also define a standardized way to determine where to split one subsidiary m-ConWIP loop from another.
If successful, the findings could help transition many small & medium sized companies in Europe working in a MTO environment from traditional, but complex, ERP system to a less complex, mostly self-regulating order release system, as an intermediate on the way to a true Industry 4.0 production environment with low costs of implementation and an “easy to understand and replicate” method.
Questions this research will answer.
I´d like to find out, wether it is possible to transfer an existing production firm from a classical ERP system with a lot of manual adjustment towards a more automated process, with drastically reduced complexity, when compared to ERP systems.
How research strategy will be designed to help answer these questions.
Based upon an existing, fictional production firm, I´d like to follow G. Romagniolis methodical approach on how to verify the proper modelling of a system, and measuring the impact of improvements as layed-out in "Design and simulation of CONWIP in the complex flexible job shop of a Make-to-Order manufacturing firm".
These described by G. Romagniolis are:
- Classify workstations and machines
- Group jobs in families
- Connect every family with an average value of Cycle Time (CT) and Sample Standard Deviation (SSD)
- Choose characteristics of the CONWIP system
- Define the cards release strategy
- Define a dispatching rule
- Build the simulation model of the current state
- Validate the simulation model
- Build the simulation model of the future state
- Simulate the future state
- Analyze results
- Possibly implement the simulated future state
How ExtendSim will be used in this project.
As seen above I´d first like to model the fictional production firm in ExtendSIm and verify, that the output-data is consitent and precise with expected values.
Once this level has been reached, ExtendSim´s scenario Manager sha´ll be utilized not only to determine the ideal level of WIP for the ConWIP loop, but also help determine to understand where the split into multiple ConWIP loops (m-ConWIP) may be reasonable.
Lastly I´d also like to utilze ExtendSims animations feature to highlight the capability of the model to self-adjust to newly arising bottlenecks.
What is unique about this project?
As far as I am aware, many ERP and Lean-Management solutions nowadays are "tailormade" solutions to one firm specifically.
While this offers great flexibility towards the needs of the company, it also inherits a high.cost structure, due to many hours needed for adaption.
I believe that a wider, more generalized approach could be beneficial to a wider audience - especially those, who´d usually not be able to afford a tailormade software solution.
Why the interest in the indicated subject?
Industry 4.0 offers a lot of chances for increased productivity with a reduced workforce and lowered costs, thus increasing the chance to compete and offer good value to customers.
Despite this, especially for smaller production firms these technologies are often cost-prohibitive, trapping them in old and labour intensive ERP systems. While those systems may still be competitive today, a move towards more automated processes is urgently needed in order to ensure being competitive beyond today.
If succesful, the results of this work could help many firms with a long tradition and great products to make the required switch and reduce costs and complexitiy. The thought of offering this help not just to one particular firm, but a wider audience and the possibility to work towards a positive impact is what motivates me to research this field.
What impact will this research make to the existing current state of knowledge?
The results of this thesis would mainly impact the MTO production firms, as described above, but possibly also a gain of knowledge towards segmented-ConWIP and when the application of such a system is useful.
Improving Toyota's Production System
Using Discrete-Event Simulation to Improve the Toyota Production System
Taha Al Bulushi
Coventry University
Information Technology for Businesses
Grant awarded: April 7, 2020
To be completed: May 9, 2020
Hypothesis.
Using ExtendSim, discrete event simulation models will be created that will model different ways the Toyota Production System can be improved.
Project description.
First, output of the project will be a value stream map (VSM) of the production system based on the information provided by the manufacturing company.
Next, a simulation model for the current state of the system will be developed based on the value-stream map. The simulation model for the current state will be analyzed and based on the findings for the analysis of the current state, improvement suggestions will be provided. The improvement suggestions will be implemented in the simulation model to create alternative scenarios.
Results of the key performance indicators (KPI’s) between the current and alternative scenarios will be compared and the best performing scenario will be suggested as the future state system.
Questions this research will answer.
How can the Toyota Production System (TPS) be improved to increase output whilst maintaining or reducing lead time and unit production cost?
How research strategy will be designed to help answer these questions.
- By referring to previous similar research studies and carrying out secondary research.
- Moreover, I am planning on carrying out an interview with an expert of the Toyota Production System to obtain the necessary data for developing the simulation models.
How ExtendSim will be used in this project.
In order to understand the behavior and performance of the system under various conditions, a computerized simulation model will be developed in the ExtendSim software based on the conceptual model created with VSM. This simulation model will enable detailed analysis of the current system as well as its performance in future states such as additional resources, increased changeover frequency or reduced change over time. Therefore, the simulation model will enable making the best decision for the production system such as future investment, maintenance strategy, changeover frequency etc. to correct issues within the current industry 4.0 Toyota Production System.
What is unique about this project?
This research has not been attempted before and it is important to carry out because one issue of TPS is that it requires suppliers to increase delivery frequency each day resulting in traffic problems and environmental issues. Moreover, using JIT causes physical strain on workers. However, it is also mentioned that lead production is only stressful due to poor management in designing and operating lean systems. This increases the need for developing an ExtendSim simulation model in order to identify issues in TPS and redesign its Toyota Manufacturing System based on improvements found using the ExtendSim model
Why the interest in the indicated subject?
One of my strongest passions and interests has always been the automobile industry, in which many car manufacturing companies have adopted the Toyota Production System. My biggest strength in my university course is Computer Simulation, which is why I decided to carry out a study where I build a simulation model for TPS to see how it can be better.
What impact will this research make to the existing current state of knowledge?
This project's main audience will be Toyota, as the findings based on which measures should be taken for Toyota to improve production efficiency. In other words, Toyota can use these findings and make tweaks such as changing the number of machines used in a production phase, time taken for a task to complete, maintenance system, and changeover frequency.
Inventory Control Theory for Reusable Articles
Inventory Control Theory for Reusable Articles in a Closed Loop Supply Chain
Eoin Glennane
Dublin City University
Master's in Renewable Energy
Grant awarded: December 14, 2020
To be completed: June 2021
Hypothesis.
The project aims to study how inventory control practices have an impact on supply chains which require reusable articles.
Project description.
Using ExtendSim, a model will be made to replicate a manufacturing process requiring reusable tools of varying quality. The models will be able to be modified to examine how changing certain parameters in the inventory control side of the model will have an impact on the production side of the model, hopefully determining optimal inventory control practices.
Questions this research will answer.
What is the optimal way to organize the purchasing of new reusable articles in this type of manufacturing scenario and why?
How research strategy will be designed to help answer these questions.
Using ExtendSim, Design Expert, and other theoretical approaches.
How ExtendSim will be used in this project.
Building the models of the manufacturing systems and testing various setups and scenarios.
What is unique about this project?
Very little research in the area, very case specific in the industry.
Why the interest in the indicated subject?
I have always had an interest in manufacturing systems, throughput analysis and inventory control and would like to pursue a career in these subjects in the future.
What impact will this research make to the existing current state of knowledge?
Adds more knowledge to a sparsely populated field. Benefits all companies downstream of the production line as no excess inventory is produced (In theory).
Nanomedicine
Inorganic nanoscale robots used for treatment and prevention of disease
Kodiak Ravicz
University of Southern California
Masters in Electrical Engineering
Grant awarded: June 2016
Project description.
Nanomedicine is a relatively new and particularly broad field. Our focus is inorganic nanoscale robots used for treatment and prevention of disease. Current challenges in this field include fabrication, biocompatibility, functional design, latency, and the physics of scale.
Our group has used ExtendSim in the past for modeling latency nanoscale drug delivery and very much appreciated its flexibility and ease of use.
Questions this research will answer.
We are trying to answer the questions of how to design and fabricate a robot with biopsy, imaging, and drug delivery capabilities.
How research strategy will be designed to help answer these questions.
We already have background research on biopsy capabilities and will conduct ongoing research into small-scale imaging techniques and alternate methods for drug delivery. We will focus on solutions that can work together within our scale.
How ExtendSim will be used in this project.
We intend to model the end-to-end process of biopsy sample collection and drug delivery, considering factors including biocompatibility, drug selection, and release timing.
What is unique about this project?
Nanomedicine is a growing field, but our research is truly unique. No one else is trying to create a robot with these specific capabilities, and our team is uniquely suited to make progress in the field.
Why the interest in the indicated subject?
Nanomedicine is a multidisciplinary field that allows us to combine knowledge from physics, engineering, mathematics, chemistry, biology, anatomy, neuroscience, and many other fields as well. Working at the intersection of all of these fields is exciting.
What will be learned from your research?
We hope to learn more about the process of design for these nanorobots.
What impact will this research make to the existing current state of knowledge?
We would like to deliver a functional nanorobot, but this is a long-term goal. Short term, we would like to push our field forward and inspire others to join this growing field of study with our results.
Publications.
Nikita Ahuja, Zhuochen Ge, Renjun Liu, Alekhya Sai, Nuduru Pati, Kodiak Ravicz, Mike Schlesinger, Shu Han Wu, Kai Xie, Mary Mehrnoosh Eshaghian-Wilner. "Toward the Design of Body Devices with Wireless Power," International Journal of Nanomedicine and Nanosurgery, April 2016.
"Review of Nanomedicine," with Amber Bhargava, Janet Cheung, Wan Lee, Kodiak Ravicz, Mike Schlesinger, Yesha Shah, Abhishek Uppal Invited for publication, International Journal of Nano Studies and Technology, to appear in 2016.
"An Introduction to Nanomedicine," with Amber Bhargava, Janet Cheung, Wan Lee, Krishna Suresh Reddy Padala, Mike Schlesinger, Yesha Shah, and Abbishek Uppall. Excerpt from "Wireless Computing in Medicine and Its Ethical/Legal Implications: From Nano to Cloud", John Wiley & Sons, Inc., July 1, 2016.
"Concluding Remarks and Future Research in Wireless Computing in Medicine," with Mike Schlesinger. Excerpt from "Wireless Computing in Medicine and Its Ethical/Legal Implications: From Nano to Cloud", John Wiley & Sons, Inc., July 1, 2016.
"Wireless Power for Body Devices," with Nikita Ahuja, Zhuochen Ge, Renjun Liu, Alekhya Sai Nuduru Pati, Kodiak Ravicz, Mike Schlesinger, Shu Han Wu. 9th Nano Congress for Next Generation, Manchester, UK, August 1-2, 2016.
"Status and Modeling of Nanomedicine," with Amber Bhargava, Janet Cheung, Wan Lee, Kodiak Ravicz, Mike Schlesinger, Yesha Shah, Abhishek Uppal. 6th Global Experts Meeting & Expo on Nanomaterials and Nanotechnology, Dubai, April 21-23, 2016.
Edited the Book Chapter by Mary Mehrnoosh Eshaghian-Wilner, Amber Bhargava, Wan Lee, Mike Schlesinger, Abbhishek Uppall and Janet Cheung, "An Introduction to Nanomedicine," in Wireless Computing in Medicine and Its Ethical/Legal Implications: From Nano to Cloud, 1st ed. New York: Wiley, 2016, ch 10.
Edited the Book Chapter by Mary Mehrnoosh Eshaghian-Wilner and Mike Schlesinger, "Concluding Remarks," in Wireless Computing in Medicine and Its Ethical/Legal Implications: From Nano to Cloud, 1st ed. New York: Wiley, 2016, ch 21.
Resource Allocation Patterns
Resource-Aware Business Process Simulation
Nehal Samy Afifi
Cairo University
PhD in Information Systems
Grant awarded: November 2017
To be completed: March 2019 extended to December 2020
Hypothesis.
There are many available tools for business process simulation, including general-purpose simulation tools, business process simulation tools, and business process modeling tools. Unfortunately, most of these tools face the problem of insufficient representation of the resources specifications and constrains.
In this research, we will focus on mending this problem by designing the resources-aware business process simulation that is able to use business process models, simulation parameters, and the required resources specifications to come with simulation results regardless the simulation tool used.
Project description.
- Study the workflow resources patterns that we will be working on.
- Survey existing simulation tools that support resources constraints.
- Compare between the surveyed tools to find the main weakness points that will help in avoiding them later, as well as finding the strength points that will be the base in the new methodology.
- Design a new or modified framework for resources patterns using simulation tool (package).
Questions this research will answer.
The main objective is specifying the missing resources allocation patterns that were ignored by other BPS approaches to come out with correct simulation results based on accurate simulation model reflecting the business process behavior to correctly predict how the real-world processes or systems will operate using specific inputs. We will depend on the workflow resources patterns as the allocation specification.
How research strategy will be designed to help answer these questions.
Various resource allocation patterns will identified, structured, modeled and, then, packed within an existing software package.
How ExtendSim will be used in this project.
Modeling workflow resources patterns using Extendsim to fill the gap in both business process simulation tools and general purpose simulation tools.
What is unique about this project?
The currently available tools have many limitations, such as: general-purpose simulation tools and business process simulation tools supports simulation but they poorly support the resources specifications and constraints while most business process modelling tools are not supporting the simulations features. So, the aim of this research is to fill the gap between tools by modelling workflow resources patterns on a general purpose simulation tool that have strong simulation capabilities.
Why the interest in the indicated subject?
To improve simulation capabilities in modeling real life business process situations.
What impact will this research make to the existing current state of knowledge?
Enabling organizations to predict how business processes perform under specific performance conditions and with accurate representation of human resources.
Updates.
July 27, 2020 -- Preparing a research paper about the implementation and results. 
Here is the latest rendition of the ExtendSim model developed for this project.
January 30, 2019 -- In this quarter, I'm working on implementing RBPSim, a business process simulation standard extension using ExtendSim. As a new case study has just been added, please extend my Research Grant an additional 6 months to September 2019. Here is the latest rendition of the ExtendSim model developed for this project.
September 3, 2018 -- The initial phase of research is complete. The next step in the research is to compare models implemented in ExtendSim 8 to those utilizing the more updated features in ExtendSim 9 - especially those features relating to the human resource perspective.
February 20, 2018 -- Since awarded the Grant in November, I have built an ExtendSim model 
and been working in extending BPSim standard with workflow resource patterns. Now I'm working on implementing the extended standard with resources using ExtendSim.
Simulation-Based Multi-Objective Optimization of the Forestry Supply Chain
Simulation based multi-objective optimization of wood supply
Karin Westlund
Uppsala Universitet
Phd in Engineering
Grant awarded: August 24, 2021
To be completed: December 31, 2024
Hypothesis.
The aim of the project is to connect simulation and multi-objective optimization, by feeding simulation models with updated and optimized data. The hypotheses is to further develop simulation modelling using both optimized, as well as stochastic, decision variables provided from other research.
Project description.
The overall aim of this research is to improve the delivery precision, delivery efficient and robustness of Swedish WSC. This will be performed using a Simulation-based Multi-objective Optimization (SMO) approach that is able to cope with changes in customer demand, stochastic deviations between planned and actual product yield as well as fluctuations in procurement prerequisites due to weather conditions.
Questions this research will answer.
- Can SMO effectively handle the stochastic nature of the forestry supply chain, providing more robust system conguration solutions and more accurate cycle time evaluations than classical optimization approaches?
- How to handle deviations between planned, mathematical optimized, deliveries and actual (stochastically affected) deliveries? When is it necessary to re-plan (re-optimize) the deliveries or accurate to continue management based on simpler decision rules?
- The influence of input data quality on optimization results, how do inaccurate data influence the planning of the system?
- How can real-time updates of input data improve the planning activities in a WSC?
How research strategy will be designed to help answer these questions.
The research methodology is based on a multi-methodology approach that is supported by the design science research paradigm. This research will use three strategies that are viewed as part of the methodology:
- the design and creation
- multiple case studies
- survey
How ExtendSim will be used in this project.
To combine simulation modelling with optimization methods on different planforms to provide new, updated or optimized input data to simulation models.
What is unique about this project?
The combination of simulation based techniques interacting with multi-objective optimization methods and platforms.
Why the interest in the indicated subject?
The overall aim of this research is to improve the delivery precision, delivery effciency and robustness of Swedish WSC.
What impact will this research make to the existing current state of knowledge?
By attaining this aim, it is expected significant economic and quality gains for the Swedish forest industry, providing better management strategies and grounds for decisions with the knowledge of how concurrent objectives capitalize on each other.
Publications.
First publications are expected December 2021.
Swarm Development
Large-scale Swarm M&S Development for Defense Scenarios Using Commercial Off-The-Shelf Software
Helen M. Vo
Johns Hopkins University • Whiting School of Engineering
Masters in Systems Engineering
Grant awarded: February 13, 2019
To be completed: November 30, 2019
Extended to: February 28, 2021
Hypothesis.
While M&S software progresses in addressing swarm development, it is believed that most distributed military applications develop their own models and simulations with minor consideration for the existing M&S software applications.
Project description.
Feasibility of Approach • An approach for determining gaps in models and simulations is viable after establishing requirements for the distributed, discrete-event, homogeneous agent-based models proposed for the studies. The requirements bound the model design and provide context to study gaps that the agent-based modeling (ABM) software platforms may have. Drafting requirements is slated to occur during the preliminary model development phase, as noted in the research schedule. Prior to drafting the requirements, reviews of swarm development frameworks specific to the ABM software will be conducted; this is commonly available through the software’s documentation and/or related research papers. Thereafter, understanding and defining a set of standard M&S workflows and entity definitions for swarms will guide requirements development.
Throughout the validation phase, collection of lessons learned will aid the compilation of barriers that currently exist to develop large-scale distributed swarm defense models. Research will periodically contribute to lessons learned.
Analysis of the simulations’ computing performance and output is achievable due to the operating systems (OS) and built-in capabilities of the ABM software offerings. Obtaining computing performance analysis of all simulation software can be gleaned by standard OS tools, which measure program run times, memory utilization and CPU usage. Simulation output will be developed within the models and results will be available after the simulation runs.
The research schedule is as follows:
- January: ABM Software Acquisition
- January-February: Preliminary Model Development with ABM Software Candidates
- 3 Basic Military Strategies involving UAVs
- Distributed UAV Design
- March: Design Review and Analysis
- Create and execute unit tests
- Address findings from review
- Create and utilize analysis tools for results
- Compare results with existing literature
- April-May: Compile findings and compose final paper
- June: Address feedback from review and submit to conference
The approach outlined above is feasible given my technical experience with M&S and software development. Additionally, my background in defense software testing and integration provides further context and application for the research focus. The caliber of tasks outlined above have reasonable level-of-effort estimates, and are on par with software development timelines and practices.
Questions this research will answer.
- How are agent-based modeling (ABM) software offerings providing federates and agents for swarm development?
- With a large-scale model and simulation, how does increasing the number of agents for the swarm model affect the computing performance (e.g., CPU usage, memory usage, and latency) and output (i.e., agents’ ability to complete the objective)?
- Given the application to defense-related scenarios, what requirements and skills are needed to utilize pre-existing ABM software? What do modelers need to know? What hardware and software resource prerequisites are needed?
- Which software and interface features are required for ABM software to produce distributed swarm models and simulations? What practices can engineers follow to utilize ABM software for swarm development?
- What improvements can ABM software offerings make to standardize swarm modeling and simulation development (i.e., utilize standard swarm terminology and provide swarm simulation analysis packages)?
How research strategy will be designed to help answer these questions.
Data Collection & Analysis Approach • Data collection will be driven by the militaristic swarm scenarios modeled and simulated in each ABM software offering. The proposed militaristic swarm scenarios are based on basic military strategies that include:
- Aerial surveillance and intelligence gathering
- Air defense
- Area denial
The military strategies will be extended to a “swarming” context and provide a basis for modeling. As several papers alluded to, the modeling terminology differs from one ABM software offering to another; during the model development phase, for each software offering, updating and deriving a mapping between terms will be conducted. Following model development, simulations with various number of agents: 100, 500, 1000, 1500, 2000, and 5000 will be executed. The results from the simulations will provide the data for quantitative analysis of each ABM software offering’s performance.
How ExtendSim will be used in this project.
ExtendSim was chosen as one of the Commercial Off-The-Shelf (COTS) M&S software offerings that I will be evaluating for performance. I will utilize ExtendSim to model the 3 airborne militaristic swarm strategies and weighing its ease of use and performance against other COTS M&S software offerings.
What is unique about this project?
The project applies 3 different, airborne military strategies to the swarm context at a large scale. This is a unique application of M&S.
Why the interest in the indicated subject?
The interest in large scale M&S for defense scenarios are two-fold.
I have been a software systems engineering, integration, and test engineer for almost 7 years at BAE Systems. In this role, I have seen the focus of defense projects turn toward modular, inexpensive solutions for modeling and simulation, as well as the adoption of COTS. At the same time, there is increased interest in swarm behavior and its application to military problems. WinForms in 2017 had a few papers/talks focused on swarming, and continued to have more dedicated tracks at this year’s INFORMS meeting.
I believe the interest is picking up or gaining more spotlight because of the advances made in distributed computing and hardware performance. The implementation or prototyping of these swarm systems are inexpensive with a plethora of open-source software and cost-effective hardware (e.g. RaspberryPi). The DoD invested in 103 Perdix drones from MIT based on the off-the-shelf performance and successfully demonstrated their launch and self-coordinated activity from FA-18 Super Hornets.
Similarly, the agent-based modeling software providers are creating swarm extensions for defense M&S. The list of ABMS is ever growing, and it is believed that most communities of swarm interest would rather utilize home-grown tools since the list can be daunting.
All of this drives me to achieve goals in this problem space.
What impact will this research make to the existing current state of knowledge?
As the focus of military strategies turns toward swarm and UAV usage, the M&S community will benefit from standardization of a consistent swarm development framework with ABM software offerings. Demonstrating ABM software performance with a defense application is relevant to the world issues today, and is important in understanding how to implement and characterize large-scale UAV swarms for a distributed perspective. My research will define a taxonomy and framework for distributed, large-scale swarm M&S within the defense context, which will provide a foundation for studying and effectively implementing swarm M&S to meet future researchers’ and engineers’ needs. Profiling the performance of current ABM software offerings is another important finding to further the field of swarm-focused modeling and simulation. The acceptance and adoption of distributed computing and high performance computing are significant variables in reevaluating the threshold that ABM researchers and engineers can reach. My research updates past findings in swarm M&S development and analysis so that swarm-focused system engineers can extend or advance the ABM software offerings.
Publications.
"Model Development for Lignocellulosic Biofuels" August 2010, (NCSU).
Updates.
December 3, 2020 -- Creating an agent-based model in ExtendSim to solve defense scenarios: intelligence, surveillance, and reconnaissance (ISR), air defense, and area denial. These scenarios expand to large numbers of agents 1000+. To date, I have been able to complete the models and simulations. I am verifying the results and performance now for presentation. Based on personal delays and thesis defense, Grant has been extended to December 31, 2020.
July 20, 2020 -- Extended Grant to December 1, 2020 as she "would like to continue and finish my model for a swarm simulation. I started evaluating the sheep and wolves example model, but need to reinstall since I had problems with my computer."
July 8, 2019 -- I modified an example ExtendSim model to understand the modeling software and how it will fit with my scenario. I have remaining tasks to make the model correspond to the other models in MATLAB and NetLogo. I have been making myself familiar with the agent-based modeling software: MATLAB SimEvents, NetLogo, and SimEvents. I drafted the scope and parameters for my first intelligence, surveillance, and reconnaissance (ISR) scenario. I have been trying to model the scenario is the ABMS software listed above.
Volcanic System Feasibility Study
Dynamic simulation of a volcanic system - a feasibility study for Taranaki, New Zealand
Melody Whitehead
Massey University
PostDoc
Grant awarded: July 17, 2020
To be completed: December 31, 2020
Hypothesis.
Feasibility study to determine the utility of ExtendSim as a dynamic (statistical) simulation tool for volcanic behaviour - an application to Taranaki, New Zealand.
Project description.
Mt Taranaki is a cone volcano in New Zealand that is thought to have last erupted 150 years ago. It is located less than 30 miles from the city of New Plymouth (population 84,400) and is classed as a hazard of national significance. 
Volcanic systems are complex, exhibit highly non-linear behaviour, and their internal structure and plumbing system(s) remain largely unobserved. To assess the hazard posed by a volcanic system to proximal populations, forecasts of future volcanic behaviour are required over a variety of time scales to inform emergency management through to infrastructure decisions.
Current whole system models are primarily statistically based and rely on previous eruption records that are often incomplete. These statistical models are exceptionally valuable for revealing hidden structures in the overall system’s dynamic behaviour. However, to extrapolate these patterns into forecasts the assumption that future volcanic behaviour will follow the same pattern must be imposed. If a set of deterministic or empirical relationships can be established that approximately represent (mimic) the information described by the statistics for previous events, these could be extrapolated into the future without this assumption.
This project is to assess the feasibility of several simulation methods (including semi-physical process models, and multiple-time scale nonlinear dynamic inversion) as an approach to modelling a volcanic system via a variety of existing software.
This work forms part of the Transitioning Taranaki to a Volcanic Future (TTVF) project and as such, will utilize data and expertise from this evolving body of work and previous studies.
Questions this research will answer.
- Can a simulation tool be used to improve volcanic activity forecasts? And if so, which existing software might be most appropriate?
- Is this approach feasible for Taranaki?
- Could this approach be applied to other volcanic systems with minimal modification?
How research strategy will be designed to help answer these questions.
Data and knowledge on the eruptive behaviour and internal dynamics of Taranaki will be collected via the TTVF project and collated from a large existing body of work. Statistical models will then be formed around these data to emulate black box dynamics and inform expected simulation outputs.
A variety of different deterministic and approximation models will then be assessed alongside these dynamics via simulation using (at minimum) MATLAB/Simulink, R, and ExtendSim to determine the feasibility of each approach and the direction of further (more complex) investigations.
How ExtendSim will be used in this project.
ExtendSim will be assessed alongside at least another two software options for ease of use, accessibility to the wider geoscientific community, process transparency, and general performance parameters.
What is unique about this project?
The application of engineering-based methods in a search for a dynamic simulation tool to a volcanic system, and the high-level of accessibility to expert knowledge and data via the TTVF project.
Why the interest in the indicated subject?
I am an aeronautical engineer working on volcanic systems. I believe we can make steps towards the dynamic simulation of specific volcanoes, I just have yet to determine how.
What impact will this research make to the existing current state of knowledge?
Best-case: one or more of the simulation tools and approaches prove viable and can be developed in further detail for Mt Taranaki such that the model of internal volcano dynamics can be utilised to inform future eruption forecasts.
Worst-case: the feasibility study finds there is insufficient information to be able to readily implement a dynamic simulation tool for a volcanic system yet but identifies important knowledge gaps and/or significant areas of missing or highly uncertain data where future studies would be of greatest benefit.
Water Storage Management
Quantifying the Reliability of a Remotely Controlled Siphon System for Dynamic Water Storage Management Using ExtendSimLinlong Bian
Florida International University
PhD in Civil and Environmental Engineering
Grant awarded: July 2, 2019
To be completed: December 31, 2019
Grant extended to: June 1, 2021
Project description.
According to the multi-wetland system and siphon assembly in the reality, an ExtendSim model is built to simulate the siphon flow rate and the time to empty to the wetlands. 
By applying the reliability theory and Monte-Carlo method, we will quantify the reliability of the siphon system. Based on safety factors, we will propose the best siphon assemble design.
These results will guide the field construction work for 12 wetlands in Texas.
For the complete research proposal, please click here.
Questions this research will answer.
- What is the global dynamic changes among the multi-wetland system? Which wetland can provide maximum mitigation effect during one flooding event, and which one provide minimum mitigation effect?
- What is the reliability of each siphon system in a wetland? What is the worst-case scenario for a wetland to lose its flooding mitigation ability?
- What is the reasonable assembly for a siphon to meet both reliability and economic requirements?
How research strategy will be designed to help answer these questions.
ExtendSim has a strong ability to depict the global dynamic changes in the simulated system which other hydraulic simulation software can never compare with. By building a multi-wetland system in ExtendSim, applying Monte-Carlo method, the worse-case scenario can be identified by observing the dynamic change process and summarize the results. After assessing the reliability of the system, the siphon components can be targeted to be improved in order to meet both reliability and economic requirements.
How ExtendSim will be used in this project.
By utilizing the continuous blocks in ExtendSim to represent the wetland, a multi-wetland system can be built. Developing some special blocks and coupling with ExtendSim blocks, a series of probability tests will be performed based on Monte-Carlo theory to determine the reliability of the siphon assembly. According to the reliability and safety factors of a siphon, propose the best assembly method.
There will be two models to build. One is to answer the reliability of one siphon and the other one to answer the reliability of all siphons in the wetland and how they affect the flooding mitigation.
What is unique about this project?
Since urban flooding is not an evitable natural hazards, our team propose a method which is to release part of the water ahead of (e.g. a few hours or a couple of days before) a heavy rainfall that is forecasted to produce flooding. To make this approach possible, a siphon system is built which can be remotely operated. These siphon is connected with wireless and can receive and perform orders from Decision Support System.
Although there are many advanced hydraulic simulation software in the industrial market, none can perform highly customized function to perform siphon. However, the ExtendSIM has highly advantage of customized design. Such advantage can achieve the function that other hydraulic simulation software cannot achieve.
Multi-wetlands are cooperated with each other to perform like a system. Therefore, observing and understanding the dynamic change in the multi-wetland system is more important for the wetland manager to come out strategy. However, these purpose can hardly achieved by hydraulics simulation software.
What impact will this research make to the existing current state of knowledge?
The results from this research will provide guidance for the 12 artificial wetlands which will be built in Texas, and further to provide management strategy for the whole cypress creek catchment with the coupling of Decision Support System.
Updates.
June 3, 2020 -- Currently, we have good research results about the reliability of the remotely controlled siphon system.
AS we want to deepen our research on it, and the research process is impacted by the Coronavirus, please extend our Research Grant to June 1, 2021.
December 26, 2019 -- I have more working load than I expected. However, this work is highly valued by my advisor. Therefore, I need to extend my research period for another six months.
There are four models which have been developed to date: siphon safety factor 1 and 2 for non-repairable and repairable system, respectively. The assumed PDF of TTF for all the system components is applied in the simulation. According to the simulation results, the system's operational reliability (average availability) significantly increases from around 60% up to 80% during 1-year life cycle for the scenario of a non-repairable system. For the repairable system, the operational reliability can maintain around 99.9%。
The next step will be to consider the operational process coupling with the reliability model.
