Results for “Resource Management Software” — Page 24

DOE OSTI2020

ddcMD: A fully GPU-accelerated molecular dynamics program for the Martini force field

We have implemented the Martini force field within Lawrence Livermore National Laboratory’s molecular dynamics program, ddcMD. The program is extended to a heterogeneous programming model so that it can exploit graphics processing unit (GPU) accelerators. In addition to the Martini force field being ported to the GPU, the entire integration step, including thermostat, barostat, and constraint solver, is ported as well, which speeds up the simulations to 278-fold using one GPU vs one central processing unit (CPU) core. A benchmark study is performed with several test cases, comparing ddcMD and GROMACS Martini simulations. The average performance of ddcMD for a protein–lipid simulation system of 136k particles achieves 1.04 µs/day on one NVIDIA V100 GPU and aggregates 6.19 µs/day on one Summit node with six GPUs. The GPU implementation in ddcMD offloads all computations to the GPU and only requires one CPU core per simulation to manage the inputs and outputs, freeing up remaining CPU resources on the compute node for alternative tasks often required in complex simulation campaigns.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2015

Towards Real-Time, On-Board, Hardware-Supported Sensor and Software Health Management for Unmanned Aerial Systems

For unmanned aerial systems (UAS) to be successfully deployed and integrated within the national airspace, it is imperative that they possess the capability to effectively complete their missions without compromising the safety of other aircraft, as well as persons and property on the ground. This necessity creates a natural requirement for UAS that can respond to uncertain environmental conditions and emergent failures in real-time, with robustness and resilience close enough to those of manned systems. We introduce a system that meets this requirement with the design of a real-time onboard system health management (SHM) capability to continuously monitor sensors, software, and hardware components. This system can detect and diagnose failures and violations of safety or performance rules during the flight of a UAS. Our approach to SHM is three-pronged, providing: (1) real-time monitoring of sensor and software signals; (2) signal analysis, preprocessing, and advanced on-the-fly temporal and Bayesian probabilistic fault diagnosis; and (3) an unobtrusive, lightweight, read-only, low-power realization using Field Programmable Gate Arrays (FPGAs) that avoids overburdening limited computing resources or costly re-certification of flight software. We call this approach rt-R2U2, a name derived from its requirements. Our implementation provides a novel approach of combining modular building blocks, integrating responsive runtime monitoring of temporal logic system safety requirements with model-based diagnosis and Bayesian network-based probabilistic analysis. We demonstrate this approach using actual flight data from the NASA Swift UAS.

Unmanned Aerial System↗

NASA NTRSDate not supplied

A Novel Architecture of JupyterHub on Amazon Elastic Kubernetes Service for Open Data Cube Sandbox

The Open Data Cube (ODC) initiative, with support from the Committee on Earth Observation Satellites (CEOS) System Engineering Office (SEO) has developed a state-of-the-art suite of software tools and products to facilitate the analysis of Earth Observation data. This paper presents a short summary of our novel architecture approach in a project related to the Open Data Cube (ODC) community that provides users with their own ODC sandbox environment. Users can have a sandbox environment all to themselves for the purpose of running Jupyter notebooks that leverage the ODC. This novel architecture layout will remove the necessity of hosting multiple users on a single Jupyter notebook server and provides better management tooling for handling resource usage. In this new layout each user will have their own credentials which will give them access to a personal Jupyter notebook server with access to a fully deployed ODC environment enabling exploration of solutions to problems that can be supported by Earth observation data.

Open Data Cube↗

DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

DOE OSTI2025

An open control sequence specification to scale building demand flexibility via analytics software

For over two decades, researchers and practitioners have showcased the ability of large commercial buildings to provide grid services by shedding or shifting load. Various utility demand response (DR) and virtual power plant (VPP) programs throughout the United States are presently utilizing these demand-side resources. However, growth of these programs have been limited, in part due to the high cost necessary to integrate the DR control strategies into the building automation system (BAS). Implementing these strategies involves adjusting control sequences, necessitating dozens of hours of customized programming per building, limiting their adoption to large organizations and progressive owners. Recent efforts by researchers and industry have demonstrated the capability of energy management and information systems (EMIS), originally designed for fault detection and diagnostics, to interface with existing BAS and perform supervisory control to optimize building operations. While these approaches are quickly being adopted by industry, demand flexibility (DF) control strategies remain limited in product offerings. One of the challenges is the lack of documented best-practice DF sequences, despite the rich literature on field implementations. This paper develops a new open-specification for a zone-based temperature adjustment shed strategy for commercial building HVAC systems, describing the specification’s implementation in two EMIS tools in both experimental and field settings. Both implementations successfully reduced electric load by at least 40% on average during the called event, while maintaining temperature limits. This study’s detailed process from specification to deployment shows the potential for scalability as well as highlights challenges related to integration with heterogeneous BAS products.

Granderson, Jessica↗

DOE OSTI2018

SNL ATDM Visualization (ECP ST Capability Assessment Report)

The SNL ATDM Data and Visualization work consolidates existing ATDM activities in scalable data management and visualization. Part of the responsibilities of the SNL ATDM Data and Visualization Project is the maintenance and development of visualization resources for ATDM applications on Exascale platforms. The ATDM Scalable Visualization project provides visualization and analysis required to satisfy the needs of the ASC/ATDM applications on next-generation, many-core platforms. This involves many activities including the re-engineering of visualization algorithms, services, and tools that enable ASC customers to carry out data analysis on ASC systems and ACES platforms. Current tools include scalable data analysis software released open source through ParaView, VTK, and Catalyst. We are also both leveraging and contributing to VTK-m, a many-core visualization library, to satisfy our visualization needs on advanced architectures. The scope of the Scalable Visualization under ATDM at SNL is R&D for the programming model and implementation of visualization code for ASC/ATDM projects and ASC/ATDM application support.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

Clinical Decision Support - Concepts of Operation

We are entering a new era in space exploration to return to the moon and explore Mars. These ambitious goals will require significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities. These constraints make it absolutely necessary to develop transformative solutions using new technologies. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses the gap Medical-701 within the Inflight Medical Conditions risk: Enhance medical capabilities within an exploration medical system. For long-duration, deep space missions, computational and data resources will play an important role in maintaining crew health, wellness and performance where the crew will need to be more self-reliant. The aim of the CDS project is to develop and provide recommended requirements for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. The CDSS is envisioned as a software-based tool that will augment a crewmembers’ knowledge, skills and abilities to assist in decision-making and crew health and performance (CHP) management thus increasing CHP systems capabilities. The human interface will be context aware and lessen the cognitive load to assimilate and use information as well as combine large disparate data sets in such a manner that provides the crew with actionable insight to decisions related to crew medical, health and performance management. Crew autonomy will be provided through a CDS that presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. The CDS project addresses the need for crew members to operate independently during long duration space exploration missions that require medical Levels of Care (LoC) V, the highest level specified by NASA-STD-3001 and described in more detail by the ExMC interpretation of LoC document (NASA/TM-2017-219290), where significant changes to in-flight and habitat medical care necessitate increasing crew autonomy in decision making and task performance. The CDS project will develop and test a series of iterative and increasingly more complex system prototypes. These annual demonstrations of the data system integration with the crew health and performance domain will inform exploration medical system requirements for an on-board Clinical Decision Support System (CDSS) through a series of use cases that guide CDS prototype functionality. CDS concepts are based on ExMC Concept of Operations documents (presented separately) and will highlight architecture extensibility to other more complex analyses and tests using core crew health and performance integrated data management, processing and visualization capabilities. This approach also establishes how externally developed analyses and approaches could be added to expand a clinical decision support system and thus highlight how a comprehensive system can be commercially and/or globally developed. The CDS project will build upon the concept of an integrated data management approach based on the Medical Data Architecture (MDA) project to more fully address challenges associated with in-flight and habitat medical, health and performance care due to constraints on mass, volume, power, crew time and medical evacuation capabilities required for medical LoC V. These requirements will be derived through systems engineering approaches and software prototype developments over the course of the multi-year CDS project to address crew health and performance decision-making and task performance, often autonomously executed by the crew, in a manner that is consistent with the appropriate medical level of care for the mission. This presentation will provide an overview of the vision for the CDS project and highlight the initial accomplishments in project planning, implementation and requirements identification in fiscal year 2020.

clinical decision support↗

NASA NTRSDate not supplied

Clinical Decision Support - Overview and Update

We are entering a new era in space exploration to return to the moon and explore Mars. These ambitious goals will require significant changes to in-flight and habitat medical care due to constraints on mass, volume, power, crew time and medical evacuation capabilities. These constraints make it absolutely necessary to develop transformative solutions using new technologies. The Exploration Medical Capability (ExMC) Element of the Human Research Program (HRP) pushes the boundary of space medical systems to advance the care of astronauts on future exploration missions beyond low Earth orbit by identifying and testing next-generation medical care and crew health maintenance technologies. The Clinical Decision Support (CDS) project addresses the gap Medical-701 within the Inflight Medical Conditions risk: Enhance medical capabilities within an exploration medical system. For long-duration, deep space missions, computational and data resources will play an important role in maintaining crew health, wellness and performance where the crew will need to be more self-reliant. The aim of the CDS project is to develop and provide recommended requirements for an in-vehicle CDSS that acts as an assistant for delivering optimal health and performance and medical care during exploration missions. The CDSS is envisioned as a software-based tool that will augment a crewmembers’ knowledge, skills and abilities to assist in decision-making and crew health and performance (CHP) management thus increasing CHP systems capabilities. The human interface will be context aware and lessen the cognitive load to assimilate and use information as well as combine large disparate data sets in such a manner that provides the crew with actionable insight to decisions related to crew medical, health and performance management. Crew autonomy will be provided through a CDS that presents knowledge and data in a context aware manner to augment a crew members’ knowledge, skills and abilities during the process of observation, orientation, decisions and action. The CDS project addresses the need for crew members to operate independently during long duration space exploration missions that require medical Levels of Care (LoC) V, the highest level specified by NASA-STD-3001 and described in more detail by the ExMC interpretation of LoC document (NASA/TM-2017-219290), where significant changes to in-flight and habitat medical care necessitate increasing crew autonomy in decision making and task performance. The CDS project will develop and test a series of iterative and increasingly more complex system prototypes. These annual demonstrations of the data system integration with the crew health and performance domain will inform exploration medical system requirements for an on-board Clinical Decision Support System (CDSS) through a series of use cases that guide CDS prototype functionality. CDS concepts are based on ExMC Concept of Operations documents (presented separately) and will highlight architecture extensibility to other more complex analyses and tests using core crew health and performance integrated data management, processing and visualization capabilities. This approach also establishes how externally developed analyses and approaches could be added to expand a clinical decision support system and thus highlight how a comprehensive system can be commercially and/or globally developed. The CDS project will build upon the concept of an integrated data management approach based on the Medical Data Architecture (MDA) project to more fully address challenges associated with in-flight and habitat medical, health and performance care due to constraints on mass, volume, power, crew time and medical evacuation capabilities required for medical LoC V. These requirements will be derived through systems engineering approaches and software prototype developments over the course of the multi-year CDS project to address crew health and performance decision-making and task performance, often autonomously executed by the crew, in a manner that is consistent with the appropriate medical level of care for the mission. This presentation will provide an overview of the vision for the CDS project and highlight the initial accomplishments in project planning, implementation and requirements identification in fiscal year 2020.

clinical decision support system↗

DOE OSTI2020

GridOPTICS/GridPACK

GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.

Palmer, Bruce↗

NASA NTRS2001

Examining Reuse in LaSRS++-Based Projects

NASA Langley Research Center (LaRC) developed the Langley Standard Real-Time Simulation in C++ (LaSRS++) to consolidate all software development for its simulation facilities under one common framework. A common framework promised a decrease in the total development effort for a new simulation by encouraging software reuse. To judge the success of LaSRS++ in this regard, reuse metrics were extracted from 11 aircraft models. Three methods that employ static analysis of the code were used to identify the reusable components. For the method that provides the best estimate, reuse levels fall between 66% and 95% indicating a high degree of reuse. Additional metrics provide insight into the extent of the foundation that LaSRS++ provides to new simulation projects. When creating variants of an aircraft, LaRC developers use object-oriented design to manage the aircraft as a reusable resource. Variants modify the aircraft for a research project or embody an alternate configuration of the aircraft. The variants inherit from the aircraft model. The variants use polymorphism to extend or redefine aircraft behaviors to meet the research requirements or to match the alternate configuration. Reuse level metrics were extracted from 10 variants. Reuse levels of aircraft by variants were 60% - 99%.

Madden, Michael M.↗

NASA NTRS2011

ISS Regenerative Life Support: Challenges and Success in the Quest for Long-Term Habitability in Space

This presentation will discuss the International Space Station s (ISS) Regenerative Environmental Control and Life Support System (ECLSS) operations with discussion of the on-orbit lessons learned, specifically regarding the challenges that have been faced as the system has expanded with a growing ISS crew. Over the 10 year history of the ISS, there have been numerous challenges, failures, and triumphs in the quest to keep the crew alive and comfortable. Successful operation of the ECLSS not only requires maintenance of the hardware, but also management of the station resources in case of hardware failure or missed re-supply. This involves effective communication between the primary International Partners (NASA and Roskosmos) and the secondary partners (JAXA and ESA) in order to keep a reserve of the contingency consumables and allow for re-supply of failed hardware. The ISS ECLSS utilizes consumables storage for contingency usage as well as longer-term regenerative systems, which allow for conservation of the expensive resources brought up by re-supply vehicles. This long-term hardware, and the interactions with software, was a challenge for Systems Engineers when they were designed and require multiple operational workarounds in order to function continuously. On a day-to-day basis, the ECLSS provides big challenges to the on console controllers. Main challenges involve the utilization of the resources that have been brought up by the visiting vehicles prior to undocking, balance of contributions between the International Partners for both systems and resources, and maintaining balance between the many interdependent systems, which includes providing the resources they need when they need it. The current biggest challenge for ECLSS is the Regenerative ECLSS system, which continuously recycles urine and condensate water into drinking water and oxygen. These systems were brought to full functionality on STS-126 (ULF-2) mission. Through system failures and recovery, the ECLSS console has learned how to balance the water within the systems, store and use water for contingencies, and continue to work with the International Partners for short-term failures. Through these challenges and the system failures, the most important lesson learned has been the importance of redundancy and operational workarounds. It is only because of the flexibility of the hardware and the software that flight controllers have the opportunity to continue operating the system as a whole for mission success.

Bazley, Jesse A.↗

DOE OSTI2025

Quantum Network Repeater Simulation Package (QNPack) v1.0.0

Existing quantum network testbeds and prototypes are typically implemented in laboratory experiments with limited functionality and operate in a tightly coupled manner. These characteristics make it difficult to evaluate the behavior of emerging quantum platforms and protocols beyond local resource limitations. The QNPack software enables full-stack modeling of quantum repeater networks that allows researchers to simulate new approaches, and understand emergent behaviors, from local to national scales. Novel capabilities include: (1) performant and accurate quantum models that can be executed as independent simulations, which will allow users to characterize specific analog quantum processes, quantum devices, and protocols, (2) a modular and extensible approach to the simulation architecture to accommodate new quantum technologies, protocols, and topologies as they are developed across the quantum repeater generations under evaluation, and (3) a focus on managing the interactions between the simulation framework sub-components so that they may be re-used and composed in flexible ways.

Kissel, Ezra [Lawrence Berkeley National Laborator↗

DOE OSTI2023

AmeriFlux FLUXNET-1F US-xTR NEON Treehaven (TREE)

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-xTR NEON Treehaven (TREE). This is the FLUXNET version of the carbon flux data for the site US-xTR NEON Treehaven (TREE) produced by applying the standard ONEFlux (1F) software. Site Description - Treehaven, situated between Rhinelander and Tomahawk, WI, is one of two relocatable sites located in NEON’s Great Lakes Domain. The Treehaven property spans 1400 acres and is owned and operated by the University of Wisconsin-Stevens Point (UWSP), College of Natural Resources. UWSP uses the property and conference center for summer field techniques courses but welcomes other educators, researchers, and the public to use and enjoy their forests, trails, and facility.

Network), NEON (National Ecological Observatory↗

NASA NTRS1994

Mapping analysis and planning system for the John F. Kennedy Space Center

Environmental management, impact assessment, research and monitoring are multidisciplinary activities which are ideally suited to incorporate a multi-media approach to environmental problem solving. Geographic information systems (GIS), simulation models, neural networks and expert-system software are some of the advancing technologies being used for data management, query, analysis and display. At the 140,000 acre John F. Kennedy Space Center, the Advanced Software Technology group has been supporting development and implementation of a program that integrates these and other rapidly evolving hardware and software capabilities into a comprehensive Mapping, Analysis and Planning System (MAPS) based in a workstation/local are network environment. An expert-system shell is being developed to link the various databases to guide users through the numerous stages of a facility siting and environmental assessment. The expert-system shell approach is appealing for its ease of data access by management-level decision makers while maintaining the involvement of the data specialists. This, as well as increased efficiency and accuracy in data analysis and report preparation, can benefit any organization involved in natural resources management.

Hall, C. R.↗

NASA NTRS2010

Web Design for Space Operations: An Overview of the Challenges and New Technologies Used in Developing and Operating Web-Based Applications in Real-Time Operational Support Onboard the International Space Station, in Astronaut Mission Planning and Mission Control Operations

The International Space Station (ISS) Operations Planning Team, Mission Control Centre and Mission Automation Support Network (MAS) have all evolved over the years to use commercial web-based technologies to create a configurable electronic infrastructure to manage the complex network of real-time planning, crew scheduling, resource and activity management as well as onboard document and procedure management required to co-ordinate ISS assembly, daily operations and mission support. While these Web technologies are classified as non-critical in nature, their use is part of an essential backbone of daily operations on the ISS and allows the crew to operate the ISS as a functioning science laboratory. The rapid evolution of the internet from 1998 (when ISS assembly began) to today, along with the nature of continuous manned operations in space, have presented a unique challenge in terms of software engineering and system development. In addition, the use of a wide array of competing internet technologies (including commercial technologies such as .NET and JAVA ) and the special requirements of having to support this network, both nationally among various control centres for International Partners (IPs), as well as onboard the station itself, have created special challenges for the MCC Web Tools Development Team, software engineers and flight controllers, who implement and maintain this system. This paper presents an overview of some of these operational challenges, and the evolving nature of the solutions and the future use of COTS based rich internet technologies in manned space flight operations. In particular this paper will focus on the use of Microsoft.s .NET API to develop Web-Based Operational tools, the use of XML based service oriented architectures (SOA) that needed to be customized to support Mission operations, the maintenance of a Microsoft IIS web server onboard the ISS, The OpsLan, functional-oriented Web Design with AJAX

Khan, Ahmed↗

NASA NTRS2011

Exploration Medical System Demonstration Project

A near-Earth Asteroid (NEA) mission will present significant new challenges including hazards to crew health created by exploring a beyond low earth orbit destination, traversing the terrain of asteroid surfaces, and the effects of variable gravity environments. Limited communications with ground-based personnel for diagnosis and consultation of medical events require increased crew autonomy when diagnosing conditions, creating treatment plans, and executing procedures. Scope: The Exploration Medical System Demonstration (EMSD) project will be a test bed on the International Space Station (ISS) to show an end-to-end medical system assisting the Crew Medical Officers (CMO) in optimizing medical care delivery and medical data management during a mission. NEA medical care challenges include resource and resupply constraints limiting the extent to which medical conditions can be treated, inability to evacuate to Earth during many mission phases, and rendering of medical care by a non-clinician. The system demonstrates the integration of medical technologies and medical informatics tools for managing evidence and decision making. Project Objectives: The objectives of the EMSD project are to: a) Reduce and possibly eliminate the time required for a crewmember and ground personnel to manage medical data from one application to another. b) Demonstrate crewmember's ability to access medical data/information via a software solution to assist/aid in the treatment of a medical condition. c) Develop a common data management architecture that can be ubiquitously used to automate repetitive data collection, management, and communications tasks for all crew health and life sciences activities. d) Develop a common data management architecture that allows for scalability, extensibility, and interoperability of data sources and data users. e) Lower total cost of ownership for development and sustainment of peripheral hardware and software that use EMSD for data management f) Provide better crew health via the reduction in crew errors, crew time, and ground time.

Chin, D. A.↗

DOE OSTI2017

Phenocams Bridge the Gap between Field and Satellite Observations in an Arid Grassland Ecosystem

Near surface (i.e., camera) and satellite remote sensing metrics have become widely used indicators of plant growing seasons. While robust linkages have been established between field metrics and ecosystem exchange in many land cover types, assessment of how well remotely-derived season start and end dates depict field conditions in arid ecosystems remain unknown. We evaluated the correspondence between field measures of start (SOS; leaves unfolded and canopy greenness >0) and end of season (EOS) and canopy greenness for two widespread species in southwestern U.S. ecosystems with those metrics estimated from near-surface cameras and MODIS NDVI for five years (2012–2016). Using Timesat software to estimate SOS and EOS from the phenocam green chromatic coordinate (GCC) greenness index resulted in good agreement with ground observations for honey mesquite but not black grama. Despite differences in the detectability of SOS and EOS for the two species, GCC was significantly correlated with field estimates of canopy greenness for both species throughout the growing season. MODIS NDVI for this arid grassland site was driven by the black grama signal although a mesquite signal was discernable in average rainfall years. Our findings suggest phenocams could help meet myriad needs in natural resource management.

ecosystem productivity↗

NASA NTRS2011

Integrated Modeling, Mapping, and Simulation (IMMS) Framework for Exercise and Response Planning

EmergenCy management personnel at federal, stale, and local levels can benefit from the increased situational awareness and operational efficiency afforded by simulation and modeling for emergency preparedness, including planning, training and exercises. To support this goal, the Department of Homeland Security's Science & Technology Directorate is funding the Integrated Modeling, Mapping, and Simulation (IMMS) program to create an integrating framework that brings together diverse models for use by the emergency response community. SUMMIT, one piece of the IMMS program, is the initial software framework that connects users such as emergency planners and exercise developers with modeling resources, bridging the gap in expertise and technical skills between these two communities. SUMMIT was recently deployed to support exercise planning for National Level Exercise 2010. Threat, casualty. infrastructure, and medical surge models were combined within SUMMIT to estimate health care resource requirements for the exercise ground truth.

Mapar, Jalal↗