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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 433 records · Page 24
All sourcesNASA NTRSDOE OSTI
NASA NTRS1971

Simulation of Mariner Mars 1971 spacecraft

Preparation for the Mariner Mars 1971 mission is reported, including an extensive training program for operations personnel during which the primary source of spacecraft data was a computer program simulating the spacecraft. The objectives of a simulation model for training purposes differed from objectives appropriate to a design or analysis model. Model subsystems were designed to provide realistic telemetry data reflecting changes due both to commands and environmental parameters affecting the spacecraft at various times during the mission. The spacecraft is modeled along two separate functional lines. Boolean operations are concentrated in the spacecraft logic model, which determines the spacecraft state or mode, while mathematical operations or algorithms are executed in computational subsystem models. Although logic parameters are interrogated as a part of each computational pass, actual logic model processing occurs only when a change-of-state input is generated by the operations organization. The program design, some of the special characteristics of each of the modeled subsystems, and how the model was used in support of mission operations training are presented.

Ausman, N. E., Jr.↗
NASA NTRS1988

Resource utilization during software development

This paper discusses resource utilization over the life cycle of software development and discusses the role that the current 'waterfall' model plays in the actual software life cycle. Software production in the NASA environment was analyzed to measure these differences. The data from 13 different projects were collected by the Software Engineering Laboratory at NASA Goddard Space Flight Center and analyzed for similarities and differences. The results indicate that the waterfall model is not very realistic in practice, and that as technology introduces further perturbations to this model with concepts like executable specifications, rapid prototyping, and wide-spectrum languages, we need to modify our model of this process.

Zelkowitz, Marvin V.↗
NASA NTRS2012

Auto Code Generation for Simulink-Based Attitude Determination Control System

This paper details the work done to auto generate C code from a Simulink-Based Attitude Determination Control System (ADCS) to be used in target platforms. NASA Marshall Engineers have developed an ADCS Simulink simulation to be used as a component for the flight software of a satellite. This generated code can be used for carrying out Hardware in the loop testing of components for a satellite in a convenient manner with easily tunable parameters. Due to the nature of the embedded hardware components such as microcontrollers, this simulation code cannot be used directly, as it is, on the target platform and must first be converted into C code; this process is known as auto code generation. In order to generate C code from this simulation; it must be modified to follow specific standards set in place by the auto code generation process. Some of these modifications include changing certain simulation models into their atomic representations which can bring new complications into the simulation. The execution order of these models can change based on these modifications. Great care must be taken in order to maintain a working simulation that can also be used for auto code generation. After modifying the ADCS simulation for the auto code generation process, it is shown that the difference between the output data of the former and that of the latter is between acceptable bounds. Thus, it can be said that the process is a success since all the output requirements are met. Based on these results, it can be argued that this generated C code can be effectively used by any desired platform as long as it follows the specific memory requirements established in the Simulink Model.

MolinaFraticelli, Jose Carlos↗
DOE OSTI2021

On the feasibility of using physics-informed machine learning for underground reservoir pressure management

In this work, we evaluate the feasibility of using physics-informed machine learning (PIML) for underground energy-related pressure management. To this end, we develop a PIML framework to manage underground reservoir pressures by training neural networks to determine fluid extraction rates for dedicated extraction wells during fluid injection operations given a range of reservoir conditions (e.g., transmissivity and storativity). We implement an automatically-differentiable analytical physics model of fluid flow in porous media within the PIML framework as a proxy for more complicated models. This allows us to execute a sufficient number of training scenarios to fully evaluate the feasibility of using PIML to support pressure management activities. We quantify the number of physics-model parameters required for automatic differentiation to become more efficient than finite-difference gradient calculations. We use a simple scenario with a single injector, extractor, and critical location for our feasibility analysis. We evaluate the effect of the size of the training dataset (i.e., the number of reservoir condition samples) on the accuracy and efficiency of the PIML framework. For an equivalent number of model evaluations, the larger training dataset took less time to train and produced a neural network that was able to more accurately manage reservoir pressures. We also evaluate the effect of the training dataset batch size (i.e., number of reservoir condition samples used to update the neural network coefficients during training; i.e., how the training dataset is partitioned). While training ran faster with larger batch sizes, they produced neural networks that managed pressures less accurately. We demonstrate the approach on a more complex scenario involving 10 injectors, 10 extractors, and 4 critical locations (a relatively high well density of 20 wells/km2). We provide the number of forward and adjoint model evaluations required in each case as an indication of the feasibility of using PIML for pressure management when more complicated physics models with longer execution times are used.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

A Fault-oblivious Extreme-scale Execution Environment

Exascale computing systems will provide a thousand-fold increase in parallelism and a proportional increase in failure rate relative to today's machines. Systems software for exascale machines must provide the infrastructure to support existing applications while simultaneously enabling efficient execution of new programming models that naturally express dynamic, adaptive, irregular computation; coupled simulations; and massive data analysis in a highly unreliable hardware environment with billions of threads of execution. We propose a new approach to the data and work distribution model provided by system software based on the unifying formalism of an abstract file system. The proposed hierarchical data model provides simple, familiar visibility and access to data structures through the file system hierarchy, while providing fault tolerance through selective redundancy. The hierarchical task model features work queues whose form and organization are represented as file system objects. Data and work are both first class entities. By exposing the relationships between data and work to the runtime system, information is available to optimize execution time and provide fault tolerance. The data distribution scheme provides replication (where desirable and possible) for fault tolerance and efficiency, and it is hierarchical to make it possible to take advantage of locality. The user, tools, and applications, including legacy applications, can interface with the data, work queues, and one another through the abstract file model. This runtime environment will provide multiple interfaces to support traditional Message Passing Interface applications, languages developed under DARPA's High Productivity Computing Systems program, as well as other, experimental programming models. We will validate our runtime system with pilot codes on existing platforms and will use simulation to validate for exascale-class platforms. In this final report, we summarize research results from the work done at the Ohio State University towards the larger goals of the project listed above.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2018

Thermal Model Performance for the James Webb Space Telescope OTIS Cryo-Vacuum Test

The James Webb Space Telescope (JWST), set to launch in early 2019, is currently undergoing a series of system-level environmental tests to verify its workmanship and end-to-end functionality. As part of this series, the Optical Telescope Element and Integrated Science Instrument Module (OTIS) Cryo-Vacuum (CV) test, the most complex cryogenic test executed to date by NASA, has recently been completed at the Johnson Space Center's Chamber A facility. The OTIS CV test was intended as a comprehensive test of the integrated instrument and telescope systems to fully understand its optical, structural, and thermal performance within its intended flight environment. Due to its complexity, extensive pre-test planning was required to ensure payload safety and compliance with all limits and constraints. A system-level pre-test thermal model was constructed which fully captured the behavior of the payload, ground support equipment, and surrounding test chamber. This thermal model simulated both the transient cooldown to and warmup from a 20K flight-like environment, as well as predicted the payload performance at cryo-stable conditions. The current work is a preliminary assessment of thermal model performance against actual payload response during the OTIS CV test. It examines both the benefits and shortcomings of assumptions made pre-test to simplify model execution when compared against test data. It explores in detail the role of temperature-dependent emissivities during transition to cryogenic temperatures, as well as the impact that model geometry simplifications have on tracking of critical hardware limits and constraints. This work concludes with a list of recommendations to improve the accuracy of thermal modeling for future large cryogenic tests. It is hoped that the insight gained from the OTIS CV test thermal modeling will benefit planning and execution for upcoming cryogenic missions.

JWST↗
NASA NTRS2018

Thermal Model Performance for the James Webb Space Telescope OTIS Cryo-Vacuum Test

The James Webb Space Telescope (JWST), set to launch in mid-2020, is currently undergoing a series of system-level environmental tests to verify its workmanship and end-to-end functionality. As part of this series, the Optical Telescope Element and Integrated Science Instrument Module (OTIS) Cryo-Vacuum (CV) test, the most complex cryogenic test executed to date by NASA, has recently been completed at the Johnson Space Center's Chamber A facility. The OTIS CV test was intended as a comprehensive test of the integrated instrument and telescope systems to fully understand its optical, structural, and thermal performance within its intended flight environment. Due to its complexity, extensive pre-test planning was required to ensure payload safety and compliance with all limits and constraints. A system-level pre-test thermal model was constructed which fully captured the behavior of the payload, ground support equipment, and surrounding test chamber. This thermal model simulated both the transient cooldown to and warmup from a 20 K flight-like environment, as well as predicted the payload performance at cryo-stable conditions. The current work is an assessment of thermal model pre-test prediction performance against actual payload response during the OTIS CV test. Overall, the thermal model performed exceedingly well at predicting schedule and payload response. Looking in depth, this work examines both the benefits and shortcomings of assumptions made pre-test to simplify model execution when compared against test data. It explores in detail the role of temperature-dependent emissivities during transition to cryogenic temperatures, as well as the impact that model geometry simplifications have on tracking of critical hardware limits and constraints. This work concludes with a list of recommendations to improve the accuracy of thermal modeling for future large cryogenic tests. The insight gained from the OTIS CV test thermal modeling will benefit planning and execution for upcoming cryogenic missions.

Testing↗
DOE OSTI2017

A characterization of workflow management systems for extreme-scale applications

We present that the automation of the execution of computational tasks is at the heart of improving scientific productivity. Over the last years, scientific workflows have been established as an important abstraction that captures data processing and computation of large and complex scientific applications. By allowing scientists to model and express entire data processing steps and their dependencies, workflow management systems relieve scientists from the details of an application and manage its execution on a computational infrastructure. As the resource requirements of today’s computational and data science applications that process vast amounts of data keep increasing, there is a compelling case for a new generation of advances in high-performance computing, commonly termed as extreme-scale computing, which will bring forth multiple challenges for the design of workflow applications and management systems. This paper presents a novel characterization of workflow management systems using features commonly associated with extreme-scale computing applications. We classify 15 popular workflow management systems in terms of workflow execution models, heterogeneous computing environments, and data access methods. Finally, the paper also surveys workflow applications and identifies gaps for future research on the road to extreme-scale workflows and management systems.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2022

A Model-Based Approach for Europa Lander Mission Concept Exploration

This study investigates the usage of a system model as a means to capture concept formulation for a potentialmission. Efforts are underway at JPL to explore thearchitectural and system concepts for a lander on Europa.Executing a mission on the surface of Europa poses uniquechallenges that will require the lander to operate with onboardautonomy that is more sophisticated than systems previouslyoperated by JPL. Current tasks to explore surface missionconcepts intend to identify concepts that enable a high degree ofonboard autonomy as well as identify the issues and technicallimitations that restrict autonomy. The Europa lander missionconcept team is developing a system model to support thisexploration.The results of this study highlight how executable systemmodeling and the associated engineering environment may beapplied to pre-project conceptual exploration. The applicationof system modeling has resulted in a central system model thatprecisely describes the concepts formulated by the EuropaLander Mission Concept Team. Documentation in the form ofdiagrams and narrative has been directly generated from thesystem model and accessible by team members in a webapplication. The executability of the system model enablesvarious analyses such as simulation of interactions betweencomponents and evaluating system behavior againstrequirements. Execution of the system model has produced statetimelines, plots of system variables, and simulation traces basedon input scenarios. The executable system model enables therapid and repeatable production of these artifacts.

Reeves, Glenn↗
NASA NTRS2018

Thermal Model Performance for the James Webb Space Telescope OTIS Cryo-Vacuum Test

The James Webb Space Telescope (JWST), set to launch in early 2019, is currently undergoing a series of system-level environmental tests to verify its workmanship and end-to-end functionality. As part of this series, the Optical Telescope Element and Integrated Science Instrument Module (OTIS) Cryo-Vacuum (CV) test, the most complex cryogenic test executed to date by NASA, has recently been completed at the Johnson Space Center’s Chamber A facility. The OTIS CV test was intended as a comprehensive test of the integrated instrument and telescope systems to fully understand its optical, structural, and thermal performance within its intended flight environment. Due to its complexity, extensive pre-test planning was required to ensure payload safety and compliance with all limits and constraints. A system-level pre-test thermal model was constructed which fully captured the behavior of the payload, ground support equipment, and surrounding test chamber. This thermal model simulated both the transient cooldown to and warmup from a 20K flight-like environment, as well as predicted the payload performance at cryo-stable conditions. The current work is a preliminary assessment of thermal model performance against actual payload response during the OTIS CV test. Overall, the thermal model performed exceedingly well at predicting schedule and payload response. Looking in depth, this work examines both the benefits and shortcomings of assumptions made pre-test to simplify model execution when compared against test data. It explores in detail the role of temperature-dependent emissivities during transition to cryogenic temperatures, as well as the impact that model geometry simplifications have on tracking of critical hardware limits and constraints. This work concludes with a list of recommendations to improve the accuracy of thermal modeling for future large cryogenic tests. It is hoped that the insight gained from the OTIS CV test thermal modeling will benefit planning and execution for upcoming cryogenic missions.

Yang, Kan↗
NASA NTRS1977

Use of the optimal control model in the design of motion cue experiments

An experiment is presented in which the effects of roll motions on human operator performance were investigated. The motion cues considered were the result of commanded vehicle motion and vehicle disturbances. An optimal control pilot-vehicle model was used in the design of the experiment and to predict system performance prior to executing the experiment. The model predictions and experimental results are compared. Seventy-eight per cent of the model predictions are within one standard deviation of the means of the experimental results. The high correlation between model predictions and system performance indicate the usefulness of the predictive model for experimental design and for prediction of pilot performance influenced by motion cues.

Junker, A. M.↗
NASA NTRS1985

DEAN: A program for dynamic engine analysis

The Dynamic Engine Analysis program, DEAN, is a FORTRAN code implemented on the IBM/370 mainframe at NASA Lewis Research Center for digital simulation of turbofan engine dynamics. DEAN is an interactive program which allows the user to simulate engine subsystems as well as a full engine systems with relative ease. The nonlinear first order ordinary differential equations which define the engine model may be solved by one of four integration schemes, a second order Runge-Kutta, a fourth order Runge-Kutta, an Adams Predictor-Corrector, or Gear's method for still systems. The numerical data generated by the model equations are displayed at specified intervals between which the user may choose to modify various parameters affecting the model equations and transient execution. Following the transient run, versatile graphics capabilities allow close examination of the data. DEAN's modeling procedure and capabilities are demonstrated by generating a model of simple compressor rig.

Sadler, G. G.↗
NASA NTRS1985

DEAN - A program for Dynamic Engine ANalysis

The Dynamic Engine Analysis Program, DEAN, is a FORTRAN code implemented on the IBM/370 mainframe at NASA Lewis Research Center for digital simulation of turbofan engine dynamics. DEAN is an interactive program which allows the user to simulate engine subsystems as well as full engine systems with relative ease. The nonlinear first order ordinary differential equations which define the engine model may be solved by one of four integration schemes, a second order Runge-Kutta, a fourth order Runge-Kutta, an Adams Predictor-Corrector, or Gear's method for still systems. The numerical data generated by the model equations are displayed a specified intervals between which the user may choose to modify various parameters affecting the model equations and transient execution. Following the transient run, versatile graphics capabilities allow close examination of the data. DEAN's modeling procedure and capabilities are demonstrated by generating a model of simple compressor rig.

Sadler, G. G.↗
NASA NTRS2009

The Transition of High-Resolution NASA MODIS Sea Surface Temperatures into the WRF Environmental Modeling System

The NASA Short-term Prediction Research and Transition (SPoRT) Center has developed a Moderate Resolution Imaging Spectroradiometer (MODIS) sea surface temperature (SST) composite at 2-km resolution that has been implemented in version 3 of the National Weather Service (NWS) Weather Research and Forecasting (WRF) Environmental Modeling System (EMS). The WRF EMS is a complete, full physics numerical weather prediction package that incorporates dynamical cores from both the Advanced Research WRF (ARW) and the Non-hydrostatic Mesoscale Model (NMM). The installation, configuration, and execution of either the ARW or NMM models is greatly simplified by the WRF EMS to encourage its use by NWS Weather Forecast Offices (WFOs) and the university community. The WRF EMS is easy to run on most Linux workstations and clusters without the need for compilers. Version 3 of the WRF EMS contains the most recent public release of the WRF-NMM and ARW modeling system (version 3 of the ARW is described in Skamarock et al. 2008), the WRF Pre-processing System (WPS) utilities, and the WRF Post-Processing program. The system is developed and maintained by the NWS National Science Operations Officer Science and Training Resource Coordinator. To initialize the WRF EMS with high-resolution MODIS SSTs, SPoRT developed the composite product consisting of MODIS SSTs over oceans and large lakes with the NCEP Real-Time Global (RTG) filling data over land points. Filling the land points is required due to minor inconsistencies between the WRF land-sea mask and that used to generate the MODIS SST composites. This methodology ensures a continuous field that adequately initializes all appropriate arrays in WRF. MODIS composites covering the Gulf of Mexico, western Atlantic Ocean and the Caribbean are generated daily at 0400, 0700, 1600, and 1900 UTC corresponding to overpass times of the NASA Aqua and Terra polar orbiting satellites. The MODIS SST product is output in gridded binary-1 (GRIB-1) data format for a seamless incorporation into WRF via the WPS utilities. The full-resolution, 1-km MODIS product is sub-sampled to 2-km grid spacing due to limitations in handling very large dimensions in the GRIB-1 data format. The GRIB-1 files are posted online at ftp://ftp.nsstc.org/sstcomp/WRF/, which is directly accessed by the WRF EMS scripts. The MODIS SST composites are also downloaded to the EMS data server, which is accessible by the WRF EMS users and NWS WFOs. The SPoRT MODIS SST composite provides the model with superior detail of the ocean gradients around Florida and surrounding waters, whereas the operational RTG SST typically depicts a relatively smooth field and is not able to capture sharp horizontal gradients in SST. Differences of 2-3 C are common over small horizontal distances, leading to enhanced SST gradients on either side of the Gulf Stream and along the edges of the cooler shelf waters. These sharper gradients can in turn produce atmospheric responses in simulated temperature and wind fields as depicted in LaCasse et al. Differences in atmospheric verification statistics over a several month study were generally small in the vicinity of south Florida; however, the validation of SSTs at specific buoy locations revealed important improvements in the biases and RMS errors, especially in the vicinity of the cooler shelf waters off the east-central Florida coast. A current weakness in the MODIS SST product is the occurrence of occasional discontinuities caused by high latency in SST coverage due to persistent cloud cover. An enhanced method developed by Jedlovec et al. (2009, GHRSST User Symposium) reduces the occurrence of these problems by adding Advanced Microwave Scanning Radiometer -- EOS (AMSR-E) SST data to the compositing process. Enhanced SST composites are produced over the ocean regions surrounding the Continental U.S. at four times each day corresponding to Terra and Aqua equator crossing times. For a given day and overpass time, both MODInd AMSR-E data from the previous seven days form a collection used in the compositing. At each MODIS pixel, cloud-free SST values from the collection are used to form a weighted average based on their latency (number of days from the current day). In this way, recent SST data are given more weight than older data. One of the primary issues involved in incorporating the AMSR-E microwave data in the composites is the tradeoff between the decreased spatial resolution of the AMSR-E data (25 km) and the increased coverage due to its near all-weather capability. Currently, the AMSR-E is given a weight of 20% compared to MODIS data, thereby preserving the spatial structure observed in the MODIS data. Day-time (night-time) AMSR-E SST data from Aqua are used with both Terra and Aqua MODIS day-time (night-time) SST data sets.

Case, Jonathan L.↗
NASA NTRS2020

Credible practice of modeling and simulation in healthcare: ten rules from a multidisciplinary perspective

The complexities of modern biomedicine are rapidly increasing. Thus, modeling and simulation have become increasingly important as a strategy to understand and predict the trajectory of pathophysiology, disease genesis, and disease spread in support of clinical and policy decisions. In such cases, inappropriate or ill-placed trust in the model and simulation outcomes may result in negative outcomes, and hence illustrate the need to formalize the execution and communication of modeling and simulation practices. Although verification and validation have been generally accepted as significant components of a model’s credibility, they cannot be assumed to equate to a holistic credible practice, which includes activities that can impact comprehension and in-depth examination inherent in the devel-opment and reuse of the models. For the past several years, the Committee on Credible Practice of Modeling and Simulation in Healthcare, an interdisciplinary group seeded from a U.S. interagency initiative, has worked to codify best practices. Here, we provide Ten Rules for credible practice of modeling and simulation in healthcare developed from a comparative analysis by the Committee’s multidisciplinary membership, followed by a large stakeholder com-munity survey. These rules establish a unified conceptual framework for modeling and simulation design, implementation, evaluation, dissemination and usage across the modeling and simulation life-cycle. While biomedical science and clinical care domains have somewhat different requirements and expectations for credible practice, our study converged on rules that would be useful across a broad swath of model types. In brief, the rules are: (1) Define context clearly. (2) Use contextually appropriate data. (3) Evaluate within context. (4) List limitations explicitly. (5) Use version control. (6) Document appropriately. (7) Disseminate broadly. (8) Get independent reviews. (9) Test competing imple-mentations. (10) Conform to standards. Although some of these are common sense guidelines, we have found that many are often missed or misconstrued, even by seasoned practitioners. Computational models are already widely used in basic science to generate new biomedical knowledge. As they penetrate clinical care and healthcare policy, contributing to personalized and precision medicine, clinical safety will require established guidelines for the credible practice of modeling and simulation in healthcare.

Credibility↗
NASA NTRS2021

Application of a Developmental Composite Material Model to Predict the Crush Response of Two Energy Absorbers

In 2012, a consortium was formed with the goal of creating a new composite material model capable of predicting the wide range of properties, accumulated damage behavior, and the many different types of failure in composites under impact loading. The material model was developed for execution in the commercially available nonlinear, explicit transient dynamic finite element code, LS-DYNA®. This material model incorporates three sub-models: deformation, damage, and failure. In addition, the model accounts for strain rate and temperature effects and relies heavily on the input of tabulated material response data. The model is designated *MAT_COMPOSITE_TABULATED_PLASTICITY_DAMAGE, or *MAT_213. Initially, *MAT_213 was developed for use with solid elements only; however, a thin shell element formulation for *MAT_213 has been adapted recently. The objective of this project was to find a suitable modeling example to investigate the capabilities and performance of *MAT_213. In 2012, two composite energy absorbers were designed and evaluated at NASA Langley Research Center through multi-level testing and simulation. The first was a conical-shaped energy absorber, designated the conusoid, which consisted of four layers of hybrid carbon-Kevlar® plain-weave fabric oriented at [+45°/-45°/-45°/+45°] with respect to the vertical direction. The second was a sinusoidal-shaped energy absorber, designated the sinusoid, which consisted of hybrid carbon-Kevlar® plain-weave fabric face sheets, two layers for each face sheet oriented at ±45° with respect to the vertical direction, and a closed-cell ELFOAM® P200 polyisocyanurate foam core. Finite element models were developed of the energy absorbers and simulations were performed using LS-DYNA®. In this paper, the development of a *MAT_213 model of a hybrid carbon-Kevlar® plain-weave fabric is presented. Next, comparisons with material characterization tests are presented. Then, test-analysis results are documented for each energy absorber as comparisons of time-history responses, as well as predicted and experimental structural deformations and progressive damage under impact loading using the *MAT_213 material model. Since a prior *MAT_58, or *MAT_LAMINATED_COMPOSITE_FABRIC material model was used in previous simulations of the energy absorbers, comparisons are made between *MAT_58 and *MAT_213 model predictions with test data. Finally, the paper includes a comprehensive list of “lessons learned,” in which a series of parametric studies are documented that were performed to investigate specific issues related to the material model. These “lessons learned” are included in hopes that they may help future *MAT_213 users.

crashworthiness, LS-DYNA transient dynamic simulat↗
DOE OSTI2025

EnergyPlus Model Context Protocol Server (EnergyPlus-MCP) v0.1

EnergyPlus-MCP is the first open-source Model Context Protocol server specifically designed for EnergyPlus building energy simulation. This innovative software enables AI assistants and other applications to interact programmatically with EnergyPlus through a standardized, secure interface, eliminating traditional technical barriers in building energy modeling. The software provides specialized tools across five functional domains: server management, model configuration and loading, comprehensive building component inspection, systematic model modification, and simulation execution with results visualization. Key features include automated HVAC system discovery and topology mapping, advanced schedule analysis, intelligent model validation, and interactive visualization capabilities. EnergyPlus-MCP's layered architecture ensures robust separation between protocol communication and domain expertise, enabling scalable deployment across organizations, educational institutions, and research teams. Unlike direct LLM approaches that suffer from inconsistent results and security gaps, EnergyPlus-MCP provides validated, reliable interactions while maintaining scientific rigor. This democratizes sophisticated building energy analysis, making EnergyPlus accessible to broader audiences through conversational interfaces and streamlined workflows.

Li, Han [Lawrence Berkeley National Laboratory (LB↗
NASA NTRS1972

A Management Information System Model for Program Management

The development of a model to simulate the information system of a program management type of organization is reported. The model statistically determines the following parameters: type of messages, destinations, delivery durations, type processing, processing durations, communication channels, outgoing messages, and priorites. The total management information system of the program management organization is considered, including formal and informal information flows and both facilities and equipment. The model is written in General Purpose System Simulation 2 computer programming language for use on the Univac 1108, Executive 8 computer. The model is simulated on a daily basis and collects queue and resource utilization statistics for each decision point. The statistics are then used by management to evaluate proposed resource allocations, to evaluate proposed changes to the system, and to identify potential problem areas. The model employs both empirical and theoretical distributions which are adjusted to simulate the information flow being studied.

Shipman, D. L.↗