Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “system engineering program”

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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Spark-Assisted HCCI Residential CHP

A transformative small spark ignition (SI) internal combustion (IC) engine fueled with natural gas was developed for combined heat and power (CHP) applications using a combination of cycle simulations, computational fluid dynamics (CFD) modeling, and engine experiments. The resulting 1 kW CHP engine was demonstrated to achieve 36.1% brake thermal efficiency (BTE) while meeting aggressive exhaust emissions targets using a low-cost three-way catalyst. Starting from a “clean-sheet” design, modeling tools were used to select the optimal engine parameters and operating characteristics. The disruptive technologies developed for the CHP system have a target lifetime of at least 10 years. The engine cost at volume of 10,000 units was estimated to be $\$$1,050. A combination of experimental and simulation results were used to identify a path to the program target of 38.6% BTE. Base engine design parameters (i.e., displacement, speed, bore, stroke, valve timings, and compression ratio) were optimized to reduce friction, heat transfer, and exhaust losses. The base clean sheet prototype engine achieved 32% BTE. Optimization of the lube oil and coolant temperatures added 1.8% BTE. The addition of exhaust gas recirculation added 1.1% BTE. Novel thermal barrier coatings (TBCs) developed over the course of the project added 1.2% BTE. Further improvements in engine friction reduction (1.3% BTE) and improved combustion (1.2% BTE) are estimated to meet the program target 38.6% BTE, while also meeting the stringent criteria pollutant emissions targets.

42 ENGINEERING↗
DOE OSTI2021

A Multi-Scale Inference, Estimation, and Prediction Engine for Earth System Modeling

We posit that AI methods can be leveraged to significantly enhance the predictive skill of forward Earth system modeling (ESM) activities. A hybrid framework incorporating traditional ESM modeling, inference methods, and AI techniques could make better use of both measured and computed information as well as computational resources by targeting inference tasks at program priorities, such as the predictability of precipitation extremes. This runtime pathway to closing the simulation/analysis-data/model improvement loop will streamline the traditional offline pathway to model improvement, which is based on domain science expertise, while suggesting guidance for further observations and measurements.

58 GEOSCIENCES↗
DOE OSTI2016

Rich-Text based PSA Model Transformation and Verification in RiskA

Nuclear Energy is one of the most possible alternative to fossil energy in large-scale. Nuclear safety is the lifeline of nuclear energy development, and has been an important part of national security, especially after the accident of Fukushima. On the basis of computer codes, reliability engineering and Probabilistic Risk Assessment (PSA) is effective methods to improve the safety of nuclear power plants. After many years of development, the methodologies, applications and relevant soft programs have been quite sufficient in the area of nuclear safety. However, it is still difficult for the current PSA technologies and software to meet the needs of dealing with the problems of quantitatively public risk assessment in the digital society. Especially, there are so many software that adopted different modeling and analyzing methods, which brings difficulties to the comparison, evaluation or verification for different software and models. By using its own academic advantages, the advanced nuclear energy research team, i.e., FDS Team has invested a few hundreds person-years of independent research and development of a reliability and probabilistic safety assessment software system RiskA. The system consists of three main functions: device reliability optimization management, probabilistic safety assessment and instantaneous risk monitoring, and the comprehensive public risk assessment in digital society. RiskA establishes an integrated risk evaluation system for the device reliability, nuclear power plant (NPP) risk monitoring and public risk assessment. Currently, RiskA has successfully been applied in more than 600 organizations and institutes from a variety of fields in 39 countries, involving nuclear, aerospace, defense and so on. For example, RiskA has been used in the safety analysis of International Thermonuclear Experimental Reactor (ITER), FDS series fusion reactor, and the Strategic Priority Research Program of Chinese Academy of Sciences 'the Future Advanced Nuclear Fission Energy - Accelerator Driven Sub-critical (ADS) transmutation system'. Also, RiskA has been used in public risk communication and risk assessment. Among them, Third Qinshan nuclear power plant Risk Monitor (TQRM), which is the China's first domestic nuclear safety analysis software used in the actual online operation, has been highly apprised by renowned experts in the field. Meanwhile, it has been identified as the first domestic nuclear power plant risk monitoring system with completely independent intellectual property rights, and has reached the international advanced level. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2019

Foundations for Engineering Education for Distributed Energy Resources (FEEDER)

Foundations for Engineering Education for Distributed Energy Resources (FEEDER), as one of the four Distributed Technology Training Consortia (DTTCs) of the Grid Engineering for Accelerated Renewable Energy Deployment (GEARED) National Network, provided programs to meet the project goals, and works closely with the GEARED National Network Administrator (NNA) to foster student competence and career interest in advanced engineering and professional skills that support a robust electrical utility sector. This educational effort also included annual gatherings to share best practices and specific advances in knowledge, instructional best practice and educational integration throughout disciplines supporting power systems analysis and integration of distributed generation, with a focus on renewable energy. This effort aligned with the goals and objectives of the Department of Energy SunShot initiative. The project goals included the creation of a larger skilled electric grid workforce that is able to manage widespread deployment of distributed energy resources by developing and sharing new courses and curricula across the participating FEEDER institutions. FEEDER was expanded to add four institutions under the Solar Training & Education for Professionals (STEP) program, with the title Strategic Expansion to Achieve GEARED Goals and award number DE- EE0007327. Program components were selected based on gap analysis and advices of FEEDER industry advisory board, with a focus on student participation in power programs, research and formative experiences that led them to successful careers in power-related industries.

14 SOLAR ENERGY↗
DOE OSTI2016

Security Hardened Cyber Components for Nuclear Power Plants: Phase I SBIR Final Technical Report

SpiralGen, Inc. built a proof-of-concept toolkit for enhancing the cyber security of nuclear power plants and other critical infrastructure with high-assurance instrumentation and control code. The toolkit is based on technology from the DARPA High-Assurance Cyber Military Systems (HACMS) program, which has focused on applying the science of formal methods to the formidable set of problems involved in securing cyber physical systems. The primary challenges beyond HACMS in developing this toolkit were to make the new technology usable by control system engineers and compatible with the regulatory and commercial constraints of the nuclear power industry. The toolkit, packaged as a Simulink add-on, allows a system designer to assemble a high-assurance component from formally specified and proven blocks and generate provably correct control and monitor code for that subsystem.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2021

Electrification FY2020 Annual Progress Report

The Electric Drive Technologies (EDT) program’s mission is to conduct early-stage research and development on transportation electrification technologies that accelerate the development of cost-effective and compact electric traction drive systems that meet or exceed performance and reliability requirements of internal combustion engine (ICE)-based vehicles, thereby enabling electrification across all light-duty vehicle types.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

NEXT Generation Energy Technologies for Connected and Automated On-Road Vehicles (NEXTCAR Phase I & II)

The Ohio State University’s ARPA-E NEXTCAR project was a multi-phase, multi-year research, development, and demonstration program focused on improving the energy efficiency of connected and automated vehicles (CAVs). The team developed and validated advanced vehicle motion and powertrain control algorithms that coordinate propulsion and automation systems to optimize energy use. Key technologies included Dynamic Skip Fire engine control, predictive eco-driving functions such as Eco-Approach and Departure (Eco-AND) and Eco-Adaptive Cruise Control (Eco-ACC), and powertrain-agnostic optimization frameworks for hybrid, plug-in hybrid, and battery electric vehicles. The project successfully demonstrated up to 30% energy-efficiency improvement during real-world testing at the Transportation Research Center and the American Center for Mobility. The outcomes provide a foundation for scalable, cost-effective deployment of energy-optimized CAV technologies across the automotive industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Data Collection and Analysis Challenges and Mitigation Strategies for Quantitative Human Factors Research Studies in Nuclear Power Plant Modernization

The United States (U.S.) Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) program Plant Modernization Pathway is conducting targeted research and development (R&D) to address aging and reliability concerns with the legacy instrumentation and control and related information systems of the U.S. LWR fleet. In this effort, the application of human factors engineering (HFE) provides an important role in ensuring new digital plant technologies enable broad innovation and business improvement with continued operational safety. Evaluation is a key activity in HFE, which often occurs iteratively through the system design lifecycle. While qualitative methods are important in collecting information of how users perform tasks through observations, quantitative methods are equally important in assessing system design based on performance. In collecting and analyzing this quantitative data, there are notable challenges in the nuclear HFE domain that may threaten the validity and reliability of the inferences made in these studies. Notable challenges include small sample size and limited resources, large error variance and small effect size, an “adding test features to losing degrees of freedom” dilemma, non-normal distribution, and heterogeneity of variance. The results in control room usability studies are often statistically non-significant, which makes it hard to interpret. This work discusses these challenges across different scientific viewpoints and provides real-world examples of these challenges in practice. Collectively, the objective of this work is to position these challenges to the larger data science community as a means of identifying future opportunities to address these issues.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2016

Infrastructure for Multiphysics Software Integration in High Performance Computing-Aided Science and Engineering

The project described in this report constructed and exercised an innovative multiphysics coupling toolkit called the Illinois Rocstar MultiPhysics Application Coupling Toolkit (IMPACT). IMPACT is an open source, flexible, natively parallel infrastructure for coupling multiple uniphysics simulation codes into multiphysics computational systems. IMPACT works with codes written in several high-performance-computing (HPC) programming languages, and is designed from the beginning for HPC multiphysics code development. It is designed to be minimally invasive to the individual physics codes being integrated, and has few requirements on those physics codes for integration. The goal of IMPACT is to provide the support needed to enable coupling existing tools together in unique and innovative ways to produce powerful new multiphysics technologies without extensive modification and rewrite of the physics packages being integrated. There are three major outcomes from this project: 1) construction, testing, application, and open-source release of the IMPACT infrastructure, 2) production of example open-source multiphysics tools using IMPACT, and 3) identification and engagement of interested organizations in the tools and applications resulting from the project. This last outcome represents the incipient development of a user community and application echosystem being built using IMPACT. Multiphysics coupling standardization can only come from organizations working together to define needs and processes that span the space of necessary multiphysics outcomes, which Illinois Rocstar plans to continue driving toward. The IMPACT system, including source code, documentation, and test problems are all now available through the public gitHUB.org system to anyone interested in multiphysics code coupling. Many of the basic documents explaining use and architecture of IMPACT are also attached as appendices to this document. Online HTML documentation is available through the gitHUB site. There are over 100 unit tests provided that run through the Illinois Rocstar Application Development (IRAD) lightweight testing infrastructure that is also supplied along with IMPACT. The package as a whole provides an excellent base for developing high-quality multiphysics applications using modern software development practices. To facilitate understanding how to utilize IMPACT effectively, two multiphysics systems have been developed and are available open-source through gitHUB. The simpler of the two systems, named ElmerFoamFSI in the repository, is a multiphysics, fluid-structure-interaction (FSI) coupling of the solid mechanics package Elmer with a fluid dynamics module from OpenFOAM. This coupling illustrates how to combine software packages that are unrelated by either author or architecture and combine them into a robust, parallel multiphysics system. A more complex multiphysics tool is the Illinois Rocstar Rocstar Multiphysics code that was rebuilt during the project around IMPACT. Rocstar Multiphysics was already an HPC multiphysics tool, but now that it has been rearchitected around IMPACT, it can be readily expanded to capture new and different physics in the future. In fact, during this project, the Elmer and OpenFOAM tools were also coupled into Rocstar Multiphysics and demonstrated. The full Rocstar Multiphysics codebase is also available on gitHUB, and licensed for any organization to use as they wish. Finally, the new IMPACT product is already being used in several multiphysics code coupling projects for the Air Force, NASA and the Missile Defense Agency, and initial work on expansion of the IMPACT-enabled Rocstar Multiphysics has begun in support of a commercial company. These initiatives promise to expand the interest and reach of IMPACT and Rocstar Multiphysics, ultimately leading to the envisioned standardization and consortium of users that was one of the goals of this project.

42 ENGINEERING↗
DOE OSTI2023

Stochastic Unit Commitment: Model Reduction via Learning

As weather-dependent renewable generation increases its share in the generation mix of most electric energy systems, a stochastic unit commitment becomes the natural day-ahead scheduling tool. However, such a tool is generally computationally intractable if a detailed uncertainty description is considered. Taking this into account, we proposed a learning method to make the stochastic unit commitment problem tractable. Here, recent advances in statistical learning and machine learning to address optimization problems can be advantageously applied to the rather intractable stochastic unit commitment problem. Considering these advances, we explore simple learning techniques to drastically reduce the size of a stochastic unit commitment problem without significantly altering its optimal solution. The considered stochastic unit commitment problem is formulated as a two-stage stochastic programming problem. The first stage represents commitment decisions, while the second one represents the operation conditions under different scenarios. Taking into account historical solved instances (or proxies for them), we reduce the size (measured by numbers of constraints and variables) of the stochastic unit commitment problem by (i) fixing unchanged binary variables and by (ii) eliminating inactive inequality constraints. Our numerical results show that the reduced problem generally requires significantly less time to solve while obtaining high-quality solutions, which are very close to or indistinguishable from the one obtained by solving the original problem. We use an Illinois 200-bus system to illustrate and characterize the performance of the proposed problem-reduction method.

42 ENGINEERING↗
DOE OSTI2017

Recovery Act – Integrated Pilot-Scale Biorefinery for Producing Ethanol from Hybrid Algae

As a scientific and engineering endeavor, the Algenol IBR Biorefinery project has been a success by almost any measure. The vision for the system evolved significantly over the course of the project, always due to recognized opportunities for improved performance, lower energy consumption, and reduced costs. Our commitment to thorough, realistic, techno-economic and life cycle assessments has been an essential element for system innovation, technology guidance, and change management of the overall facility. The biological tools developed during this program for cyanobacteria are second to none, and are the primary reason for the remarkable improvements in organism performance. The breakthrough was the successful transformation of our most robust wild type organism (AB1) early in 2012. That was followed by a series of improvements over the next several years that produced strains wherein over 80% of the fixed carbon was converted into ethanol. At the same time, our expertise in cultivation, physiology, process engineering, CO2 management, and photobioreactor design and manufacturing grew at a comparable pace. We learned enormous amounts from the various upsets, weather variations, contamination events, and new technology related disappointments. We overcame those challenges to produce fuel grade ethanol with a low carbon footprint, and are within striking distance of economic viability even with the challenges of low fossil fuel prices.

09 BIOMASS FUELS↗
DOE OSTI2020

An Application of ASP in Nuclear Engineering: Explaining the Three Mile Island Nuclear Accident Scenario

Abstract The paper describes an ongoing effort in developing a declarative system for supporting operators in the Nuclear Power Plant (NPP) control room. The focus is on two modules: diagnosis and explanation of events that happened in NPPs. We describe an Answer Set Programming (ASP) representation of an NPP, which consists of declarations of state variables, components, their connections, and rules encoding the plant behavior. We then show how the ASP program can be used to explain the series of events that occurred in the Three Mile Island, Unit 2 (TMI-2) NPP accident, the most severe accident in the USA nuclear power plant operating history. We also describe an explanation module aimed at addressing answers to questions such as “why an event occurs?” or “what should be done?” given the collected data.

Computer Science↗
DOE OSTI2016

Computer Codes V and V Tests with a Large-Scale Sodium Thermal-Hydraulic Test Facility (STELLA)

The Korea Atomic Energy Research Institute (KAERI) is carrying out the design of a 'Prototype Generation IV Sodium-cooled Fast Reactor (PGSFR)' in cooperation with Argonne National Laboratory (ANL) in the US. In regard to computer codes V and V, a large-scale sodium thermal-hydraulic test program is currently being progressed in parallel with the PGSFR design, which is called STELLA (Sodium Test Loop for Safety Simulation and Assessment). The final objective of this program is to collect a separate and integral effect test database to validate the safety analysis codes and other thermal hydraulic design codes. In the first phase of the STELLA program, the sodium component test loop (hereafter called STELLA-1) was constructed at the KAERI site, and it has been used for performance tests of key sodium heat exchangers in PGSFR. Since this sodium test loop is basically for separate effects tests to verify the performance of key sodium components, the test database obtained from STELLA-1 has been used for the V and V of safety codes as well as heat exchanger design codes. The second phase of the program aiming at an integral effect test is called STELLA-2, which will be used for synthetic review of the key safety issues of PGSFR. The basic and detailed design phases of the STELLA-2 test facility are underway in accordance with the specific design requirements reflecting the whole design features of PGSFR. The facility installation is scheduled to be completed by 2018. Then the main experiments including the start-up tests will begin and the first integral effect test database will be constructed by the end of 2019. Based on the STELLA-2 platform, a simulation of the PGSFR transient will be made to evaluate the plant dynamic behaviors and demonstrate the decay heat removal performance. Multi-dimensional effects coming from a large sodium pool system will be identified as well. The test database obtained from the STELLA-2 experiment will be used for the validation of the safety analysis codes and other thermal hydraulics codes, and this project finally contributes to the specific design phase of PGSFR. This paper presents both the results of heat transfer tests for the key sodium heat exchangers using STELLA-1 and the first results of heat exchanger design codes V and V. The recent progress of the engineering design for the STELLA-2 test section is introduced and its specific design parameters are also presented in this paper with detailed evaluation results of their scaling distortions. A large-scale sodium thermal-hydraulic test program (STELLA) was introduced with the specific activities for separate and integral effects tests. The test database obtained from STELLA-1 was successfully used to validate both the heat exchanger design and safety analysis codes. Specific design features of the integral effects test facility (STELLA- 2) with a scaling ratio of 1/5 in length and 1/125 in volume were also presented. Validation of the STELLA-2 facility design is underway using system codes and CFD tools. Dedicated water-mockup experiments to verify the scaling design of key subsystems are currently being conducted as well. (authors)

42 ENGINEERING↗
DOE OSTI2016

A model of polarized-beam AGS in the ray-tracing code Zgoubi

A model of the Alternating Gradient Synchrotron, based on the AGS snapramps, has been developed in the stepwise ray-tracing code Zgoubi. It has been used over the past 5 years in a number of accelerator studies aimed at enhancing RHIC proton beam polarization. It is also used to study and optimize proton and Helion beam polarization in view of future RHIC and eRHIC programs. The AGS model in Zgoubi is operational on-line via three different applications, ’ZgoubiFromSnaprampCmd’, ’AgsZgoubiModel’ and ’AgsModelViewer’, with the latter two essentially interfaces to the former which is the actual model ’engine’. All three commands are available from the controls system application launcher in the AGS ’StartUp’ menu, or from eponymous commands on shell terminals. Main aspects of the model and of its operation are presented in this technical note, brief excerpts from various studies performed so far are given for illustration, means and methods entering in ZgoubiFromSnaprampCmd are developed further in appendix.

43 PARTICLE ACCELERATORS↗
DOE OSTI2017

Lubricant Formulations to Enhance Engine Efficiency in Modern Internal Combustion Engines

The research program presented aimed to investigate, develop, and demonstrate low-friction, environmentally-friendly and commercially-feasible lubricant formulations that would significantly improve the mechanical efficiency of modern engines without incurring increased wear, emissions or deterioration of the emission-aftertreatment system.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

ANS Winter 2024 Summary: MCCAFE: The Monte Carlo Constructor for ATR Fuel Elements

The Irradiation Experiment Neutronics Analysis Department at Idaho National Laboratory (INL) has implemented a new analysis workflow for experiments in the Advanced Test Reactor (ATR). One key piece of this workflow is the Monte Carlo Constructor for ATR Fuel Elements, or MCCAFE. For each ATR operating cycle, the Reactor and Nuclear Safety Engineering (RNSE) Department first solves the core in eigenvalue mode and depletes the driver fuel materials. In a separate calculation, neutronics analysts model and deplete the materials of one or more irradiation experiments, usually in a series of fixed-source Monte Carlo N-Particle (MCNP) models of the ATR for neutron transport calculations. It was desirable to use the results of the former calculations to inform the models of the latter. MCCAFE is a Python program developed using American Society of Mechanical Engineers Nuclear Quality Assurance-1 procedures at INL. Its purpose is to take the calculated results from the RNSE depletion solutions and the measured or projected operating parameters from the Nuclear Data Management and Analysis System (NDMAS) to generate fixed-source models of the ATR core at given points in time across one or more cycles.

99 - GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Grand Challenges in the Science of Wind Energy

The energy system of the future that depends on 80% or more renewable energy will put new demands on the wind systems that support it. There are significant areas of scientific uncertainly that need to be addressed to enable the innovation required for success. This presentation, based on a 2019 article in Science, lays out those areas of scientific challenges and proposes an integrated wind energy discipline that encompasses the needed research.

49 EE - Wind and Water Power Program - Wind (EE-4W↗