Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Scenario optimization”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Implementation of a Metamodel-Based Optimization for the Design of a High Power Density Wound Field Traction Motor

Traction motors onboard electric vehicles (EVs) are faced with ever-increasing power density requirements and cost reduction challenges. Although permanent magnet (PM) traction motors have been favored for their potential of higher power densities, the price and supply volatility of PM materials are the major drawbacks. Instead of a single load point, the performance of a traction motor needs to be optimized over various combinations of torque and speed to represent real-world vehicular driving scenarios, which tends to be a time-consuming task with direct optimizations. In this study, as a PM-free solution, a wound field synchronous motor (WFSM) is designed and optimized using a metamodel-based approach to maximize its efficiency over a custom set of load points, while utilizing a fully per-unitized geometry template. The workflow has proven to be timesaving and the optimal design is prototyped and tested.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2016

A Quasi-Global Approach to Improve Day-Time Satellite Surface Soil Moisture Anomalies through the Land Surface Temperature Input

Passive microwave observations from various spaceborne sensors have been linked to the soil moisture of the Earth's surface layer. A new generation of passive microwave sensors are dedicated to retrieving this variable and make observations in the single theoretically optimal L-band frequency (1-2 GHz). Previous generations of passive microwave sensors made observations in a range of higher frequencies, allowing for simultaneous estimation of additional variables required for solving the radiative transfer equation. One of these additional variables is land surface temperature, which plays a unique role in the radiative transfer equation and has an influence on the final quality of retrieved soil moisture anomalies. This study presents an optimization procedure for soil moisture retrievals through a quasi-global precipitation-based verification technique, the so-called Rvalue metric. Various land surface temperature scenarios were evaluated in which biases were added to an existing linear regression, specifically focusing on improving the skills to capture the temporal variability of soil moisture. We focus on the relative quality of the day-time (01:30 pm) observations from the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), as these are theoretically most challenging due to the thermal equilibrium theory, and existing studies indicate that larger improvements are possible for these observations compared to their night-time (01:30 am) equivalent. Soil moisture data used in this study were retrieved through the Land Parameter Retrieval Model (LPRM), and in line with theory, both satellite paths show a unique and distinct degradation as a function of vegetation density. Both the ascending (01:30 pm) and descending (01:30 am) paths of the publicly available and widely used AMSR-E LPRM soil moisture products were used for benchmarking purposes. Several scenarios were employed in which the land surface temperature input for the radiative transfer was varied by imposing a bias on an existing regression. These scenarios were evaluated through the Rvalue technique, resulting in optimal bias values on top of this regression. In a next step, these optimal bias values were incorporated in order to re-calibrate the existing linear regression, resulting in a quasi-global uniform LST relation for day-time observations. In a final step, day-time soil moisture retrievals using the re-calibrated land surface temperature relation were again validated through the Rvalue technique. Results indicate an average increasing Rvalue of 16.5%, which indicates a better performance obtained through the re-calibration. This number was confirmed through an independent Triple Collocation verification over the same domain, demonstrating an average root mean square error reduction of 15.3%. Furthermore, a comparison against an extensive in situ database (679 stations) also indicates a generally higher quality for the re-calibrated dataset. Besides the improved day-time dataset, this study furthermore provides insights on the relative quality of soil moisture retrieved from AMSR-E's day- and night-time observations.

soil moisture↗
DOE OSTI2022

Optimal band selection for target detection with a LWIR multispectral imager

Multispectral imaging can offer many benefits in cost, complexity, resolution, size, weight, and power, relative to hyperspectral imaging. When designing a multispectral system, spectral bandpasses can be selected using optimization algorithms configured to maximally separate target detection scores between target and background regions. A hyperspectral image (HSI) can serve as the source of data from which band groupings can be tested for optimality. The output of an adaptive cosine estimator target detection algorithm is used in an objective function. Three optimization algorithms are compared: particle swarm, dual annealing, and differential evolution. A global optimum is also found using a brute force approach on the Livermore Computing Syrah supercomputer. Three materials are investigated: calcite, gypsum, and limestone. This is done for 3-, 4-, and 5-band systems. The data originate from a longwave infrared HSI of a material display board. The optimization algorithms were run 30 times for every scenario. Performance statistics (maximum, minimum, mean, standard deviation, and median) based on the separation values are given. Additional characterization was performed using receiver operator characteristic (ROC) curves and the area under the ROC curve. While good performance was obtained for the three optimization algorithms, the dual annealing algorithm produced the highest and most consistent detection separation scores on average.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Development of Digital Twin-Informed Predictive Maintenance for Critical Components in Advanced Reactors

Small modular reactors (SMRs) and microreactors, along with other advanced reactor (AR) technologies, are key to the future of nuclear energy. For these systems to achieve low operating costs, high reliability, and flexibility across applications, their operation and maintenance must be optimized. Digital twin (DT) technology is one of the technologies that enables real-time (or faster than real-time) monitoring and prognosis of critical components which are vital for operational efficiency, low costs, and enhanced safety of ARs, accelerating their deployment. DT technology provides dynamic virtual representation of physical assets by integrating real-time data, physics-based models, and advanced analytics, which is critical to optimizing the performance of the entire energy system throughout the life cycle. DTs empower engineers and operators to virtually explore different scenarios, configurations, and control strategies, allowing for the identification of optimal solutions that maximize reactor efficiency, safety, and economics.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

HIPPO – A Software Platform for Electricity Market Research and Development

The goal of this project is to provide Regional transmission organizations (RTOs) and independent system operators (ISOs) a market design and prototyping software, High-Performance Power-Grid Optimization (HIPPO), that they can evaluate electricity market design options, calculate market planning strategies and operational performance. With the high standards and strict reliability requirements for operating power systems, impacts of new technologies need to be fully investigated prior to any consideration for adoption. A market design and prototyping software tool which can be used to prototype electricity market design options, to calculate market planning strategies and operational performance with high precision, and to investigate the impacts for integrating future power grid technologies will be valuable to RTOs/ISOs who operate power systems, to vendors like GE and ABB who provide the market solvers, and to market participants and researchers who are actively doing market research. HIPPO is a such tool that can be used to improve the current market operations and provide capabilities for rigorous forward-looking design and prototyping of next-generation energy markets. HIPPO has a high-resolution model for the day-ahead SCUC, which was validated with MISO and GE-Grid Solutions. HIPPO is built with parallel and distributed computing capabilities and can be executed in both multi-thread and high-performance computing (HPC) settings. This capability provides fast solution speed necessary to handle the larger and more complex SCUC problems of real-world cases and the potentially growing size and complexity of future scenarios. In addition, HIPPO has a concurrent optimizer (CO) which manages multiple algorithm executions simultaneously and leverages the advantages from different algorithms. This structure provides flexibility to better benchmark competing approaches. Highly accurate market model, fast solution technologies and flexible model and algorithm control are the features which will make HIPPO an extensible platform for developing and testing multiple approaches to meet a wide range of future market needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Evaluation of Physical Security Risk for Potential Implementation of FLEX using Dynamic Simulation Methods

The requirements for United States nuclear power plants to maintain a large onsite physical security force contribute to their large operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability Program Physical Security Pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. This pathway will analyze and minimize the conservatisms built into current security postures in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within this pathway has successfully developed a dynamic force-on-force (FOF) modeling framework using various computer simulation tools and integrated them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an overview of lessons learned in applying a dynamic computational framework that links results from a commercially available FOF simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework. Previous reports described how a user could integrate their plant-specific FOF models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as Computer Aided Fault Tree Analysis System or Systems Analysis Programs for Hands-on Integrated Reliability Evaluations, and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance of the use of the framework. Such an assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants. NOTE: The work performed in this report is based on a generic EMRALD model with actual plant data used for the analysis. However, only the generic model and general results of the analysis are in the report. No plant’s sensitive information is discussed in this report. The discussion shows examples of insights that can be obtained from the MASS-DEF methodology.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

An Evaluation of The Dynamic Physical Security Risk Assessment Methodology for Fleet-Wide Applications

The requirements for U.S. nuclear power plants to maintain a large onsite physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This integrated process for physical security analysis is named Modeling and Analysis for Safety Security using Dynamic EMRALD Framework (MASS-DEF). This document provides an update on the progress in applying the MASS-DEF process to an operating commercial nuclear power plant as well as additional industry feedback regarding use of the tool for other physical security risk-informed topics. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, and integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5 or MAAP. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report is an update the progress of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report also provides an update to the procedural guidance for the MASS-DEF process and an overview of the generic models available for use by utilities. This report does not contain any plant’s sensitive information and/or safeguards information. This study’s purpose was to verify that the results achieved using generic models are similar to actual plant results and refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Plant-specific Model and Data Analysis using Dynamic Security Modeling and Simulation

The requirements for U.S. nuclear power plants to maintain a large on-site physical security force contribute to their high operational costs. The cost of maintaining the current physical security posture is approximately 10% of the overall operation and maintenance budget for commercial nuclear power plants. The goal of the Light Water Reactor Sustainability (LWRS) program’s physical security pathway is to develop tools, methods, and technologies and provide the technical basis for an optimized physical security posture. The conservatisms built into current security postures may be analyzed and minimized in order to reduce security costs while still ensuring adequate security and operational safety. The research performed at Idaho National Laboratory within LWRS program’s physical security pathway has successfully developed a dynamic force-on-force modeling framework using various computer simulation tools and integrating them with the dynamic assessment Event Modeling Risk Assessment using Linked Diagrams (EMRALD) tool. This document provides an update on the progress in applying a dynamic computational framework that links results from a commercially available force-on-force simulation tool, a commercially available thermal-hydraulic tool, and EMRALD to an operating commercial nuclear power plant. This report is only a summary of the progress and does not contain specific modeling results as those contain sensitive security information. This process of including plant procedures and multiple analysis results is being called Modeling and Analysis for Safety Security using Dynamic EMRALD Framework or MASS-DEF. Previous reports described how a user could integrate their plant-specific force-on-force models with the dynamic simulation tool EMRALD, model operator actions, integrate with probabilistic risk assessment tools, such as CAFTA (Computer Aided Fault Tree Analysis System) or SAPHIRE (Systems Analysis Programs for Hands-on Integrated Reliability Evaluations), and with thermal-hydraulic tools, such as RELAP-5. Previous reports applied various combinations of available simulations codes with EMRALD using generic plant models to demonstrate how to perform the analysis. This report documents the results of applying the dynamic computational framework to an actual nuclear facility using their security scenarios and timelines. This report does not contain any plant's sensitive information and/or Safeguards Information. The purpose of this study was to verify that results achieved using generic models are similar to actual plant results and to refine our guidance on the use of the framework. This assessment enables further analysis, such as what-if scenarios and staff-reduction evaluation, thereby optimizing physical security at plants.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Future marine biofuels in the port of Seattle region

Marine transportation, a vital global sector, emits 3% of global annual greenhouse gas emissions, which are predicted to increase in the future. Marine biofuels derived from biomass or waste sources like wood residue, waste oil and municipal solid waste can be used for decarbonization. However, limited studies have explored if sufficient marine biofuels could be produced and supplied to major regional ports given feedstock, supply chain and technological constraints. We fill this gap by evaluating the feasibility of supplying marine biofuels to the Port of Seattle. The Regional Bio-Economy Model (RBEM) and the Freight and Fuel Transportation Optimization Tool (FTOT) are used to build scenarios for simulating marine biofuel production in the Port region. We harmonized technoeconomic assumptions for RBEM and FTOT, input FTOT feedstock utilization and routing outputs into RBEM, and modelled conversion, feedstock, and policy scenario variations in RBEM. In RBEM, overall biofuel production was constrained primarily by the biofuel cost, and then by feedstock availability. Providing policy incentives and reducing permitting time frames alleviated these constraints and spurred the buildout of a robust industry through industrial learning dynamics in the initial years. With these measures in place, the RBEM results show that 100% of fuel demand at the Port can be supplied by biofuels with policy incentives and suitable technoeconomic conditions, but the addition of transportation cost considerations using FTOT led to 27.8% of demand being able to be met by biofuels at reasonable fuel delivery cost.

09 BIOMASS FUELS↗
DOE OSTI2023

AI-Based Optimal Design and Controls Can Greatly Reduce Carbon Emissions and Enhance Resilience in Residential Communities in Cold Climates

Net-zero energy residential communities are crucial for achieving decarbonization goals, but the high-penetration photovoltaic (PV) in those communities is posing challenges to the distribution grid. Traditional design and operation of net-zero communities rely on rule-of-thumb methods and may not work in complex scenarios. Artificial intelligence and machine learning methods can optimally size PV for net-zero energy, identify user preferences and usage patterns, and fully unlock the potential of distributed energy resources to address distribution grid issues.

artificial intelligence↗
DOE OSTI2020

Power System Resilience Enhancement in Typhoons Using a Three-Stage Day-Ahead Unit Commitment

In this work, we propose a three-stage resilient unit commitment model which considers uncertain typhoon paths and line outages to improve the power system resilience against typhoon events. The proposed solution coordinates resources in response to the worst-case scenario for each possible typhoon path. The optimal decision is based on the characterization of the power system schedule into three stages of preventive control, emergency control, and restoration. Preventive control is performed before the typhoon occurs by quickly adjusting the three-stage resilient unit commitment schedule; emergency control is conducted during the typhoon by shedding local loads to meet the power balance, while other control strategies are assumed to be unavailable due to possible interruptions in the communication system; restoration is realized after the typhoon, when resources are optimally dispatched to repair the outages of critical devices and recover the normal operation state of the power system quickly. Considering the typhoon path uncertainty, we have introduced a stochastic model for possible typhoon paths where all possible affected lines along each typhoon path are assumed to be on outage during the typhoon. Accordingly, we explore the strategy for co-optimizing the three stages in unit commitment. The proposed model is tested on the IEEE 118-bus system and the real-world provincial system to verify its effectiveness.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows (IPPD) (Final Report)

This report details the accomplishments from the ASCR funded project “Integrated End-to-end Performance Prediction and Diagnosis for Extreme Scientific Workflows” under the award numbers FWP-66406 and DE-SC0012630, with a focus on the UC San Diego (Award No. DE-SC0012630) part of the accomplishments. We refer to the project as IPPD. The main activities of IPPD were centered on the development and integration of provenance information to capture empirically workflow information and identify the sources of bottlenecks as well as variability, and modeling and simulation to provide insights and predictively explore multiple scenarios for development of advanced techniques for optimization of resources and workflow execution. After a Phase I of the project, a Phase II effort focused on three major aspects: a) observe how data is generated, distributed, and used; b) analyze how data is (repeatedly) consumed with a focus both on repeated patterns and anomalies; and c) explore how to optimize data motion. The project leveraged and extended our existing tools with new research and demonstrated our work on the Belle II workflow suite as well as on workflows from NSLS-II.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1995

Rapid Mars transits with exhaust-modulated plasma propulsion

The operational characteristics of the Exhaust-Modulated Plasma Rocket are described. Four basic human and robotic mission scenarios to Mars are analyzed using numerical optimization techniques at variable specific impulse and constant power. The device is well suited for 'split-sprint' missions, allowing fast, one-way low-payload human transits of 90 to 104 days, as well as slower, 180-day, high-payload robotic precursor flights. Abort capabilities, essential for human missions, are also explored.

Chang-Diaz, Franklin R.↗
NASA NTRS2004

Modelling and Analysis of a Regenerative Fuel Cell Propulsion System for a High Altitude Long Endurance UAV

In the search to bridge current gaps in surveillance and communication technologies, a new type of, aircraft is currently undergoing design. The idea of a High Altitude Long Endurance (HALE) aircraft is already a few decades old, but has only recently become realizable. A relay and collector of information at altitudes of 65,000 feet and higher could greatly improve standards of data exchange, homeland security, and research of the air, land and sea. NASA, as a major force in propulsion research, is exploring methods of powering an autonomous aircraft for days, weeks, or even months without refueling. Such a task requires not only high energy density, but also the ability to make use of renewable energy sources to regenerate power. Hydrogen is one of the most energy dense fuels available. Fuel cells make use of hydrogen by harnessing the energy released as it combines with oxygen to produce electricity and water. Fuel cells are envisioned to occupy future propulsion systems in cooperation with solar cells where the photovoltaic arrays harness sunlight into power which can electrolize the water byproduct into reusable hydrogen and oxygen. Modeling this type of system requires adequate assumptions of support hardware and daily transients in operation. The performance of a regenerative fuel cell propulsion system lies in the flight characteristics (altitude, density, temperature, latitude, etc.). Each subsystem is defined by many parameters which can be varied across wide ranges. Statistical and probabilistic analyses bring forward a wealth of information that can be utilized in the design process. This is necessary since the required technologies are relatively young and barely, if yet, capable. Once the modeling is complete, a design space exploration of this highly constrained scenario can be utilized to find the optimal design. The model will become an interactive environment with which experiments and tests can be run. When linked

Simpson, Mike B.↗
NASA NTRS2007

Improved Modeling of Land-Atmosphere Interactions using a Coupled Version of WRF with the Land Information System

The exchange of energy and moisture between the Earth's surface and the atmospheric boundary layer plays a critical role in many hydrometeorological processes. Accurate and high-resolution representations of surface properties such as sea-surface temperature (SST), vegetation, soil temperature and moisture content, and ground fluxes are necessary to better understand the Earth-atmosphere interactions and improve numerical predictions of weather and climate phenomena. The NASA/NWS Short-term Prediction Research and Transition (SPORT) Center is currently investigating the potential benefits of assimilating high-resolution datasets derived from the NASA moderate resolution imaging spectroradiometer (MODIS) instruments using the Weather Research and Forecasting (WRF) model and the Goddard Space Flight Center Land Information System (LIS). The LIS is a software framework that integrates satellite and ground-based observational and modeled data along with multiple land surface models (LSMs) and advanced computing tools to accurately characterize land surface states and fluxes. The LIS can be run uncoupled to provide a high-resolution land surface initial condition, and can also be run in a coupled mode with WRF to integrate surface and soil quantities using any of the LSMs available in LIS. The LIS also includes the ability to optimize the initialization of surface and soil variables by tuning the spin-up time period and atmospheric forcing parameters, which cannot be done in the standard WRF. Among the datasets available from MODIS, a leaf-area index field and composite SST analysis are used to improve the lower boundary and initial conditions to the LIS/WRF coupled model over both land and water. Experiments will be conducted to measure the potential benefits from using the coupled LIS/WRF model over the Florida peninsula during May 2004. This month experienced relatively benign weather conditions, which will allow the experiments to focus on the local and mesoscale impacts of the high-resolution MODIS datasets and optimized soil and surface initial conditions. Follow-on experiments will examine the utility of such an optimized WRF configuration for more complex weather scenarios such as convective initiation. This paper will provide an overview of the experiment design and present preliminary results from selected cases in May 2004.

Case, Jonathan L.↗
NASA NTRS2011

Common Bolted Joint Analysis Tool

Common Bolted Joint Analysis Tool (comBAT) is an Excel/VB-based bolted joint analysis/optimization program that lays out a systematic foundation for an inexperienced or seasoned analyst to determine fastener size, material, and assembly torque for a given design. Analysts are able to perform numerous what-if scenarios within minutes to arrive at an optimal solution. The program evaluates input design parameters, performs joint assembly checks, and steps through numerous calculations to arrive at several key margins of safety for each member in a joint. It also checks for joint gapping, provides fatigue calculations, and generates joint diagrams for a visual reference. Optimum fastener size and material, as well as correct torque, can then be provided. Analysis methodology, equations, and guidelines are provided throughout the solution sequence so that this program does not become a "black box:" for the analyst. There are built-in databases that reduce the legwork required by the analyst. Each step is clearly identified and results are provided in number format, as well as color-coded spelled-out words to draw user attention. The three key features of the software are robust technical content, innovative and user friendly I/O, and a large database. The program addresses every aspect of bolted joint analysis and proves to be an instructional tool at the same time. It saves analysis time, has intelligent messaging features, and catches operator errors in real time.

Imtiaz, Kauser↗
NASA NTRS2012

JELC-LITE: Unconventional Instructional Design for Special Operations Training

Current special operations staff training is based on the Joint Event Life Cycle (JELC). It addresses operational level tasks in multi-week, live military exercises which are planned over a 12 to 18 month timeframe. As the military experiences changing global mission sets, shorter training events using distributed technologies will increasingly be needed to augment traditional training. JELC-Lite is a new approach for providing relevant training between large scale exercises. This new streamlined, responsive training model uses distributed and virtualized training technologies to establish simulated scenarios. It keeps proficiency levels closer to optimal levels -- thereby reducing the performance degradation inherent in periodic training. It can be delivered to military as well as under-reached interagency groups to facilitate agile, repetitive training events. JELC-Lite is described by four phases paralleling the JELC, differing mostly in scope and scale. It has been successfully used with a Theater Special Operations Command and fits well within the current environment of reduced personnel and financial resources.

Friedman, Mark↗