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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

INTEGRATION OF DATA ANALYTICS WITH SYSTEM HEALTH PROGRAMS

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry developed and regulatory programs. However, these programs have proven to be labor intensive and expensive. There is an opportunity to significantly enhance the collection, analysis, and use of this information to provide more cost-effective plant operation. Additionally, there is an acute industry need to leverage advanced technology to reduce costs and improve operational effectiveness. The goal of this paper is to provide effective and efficient analytical methods and tools to support risk-informed decisions for the equipment reliability and asset management programs at nuclear power plants. This is accomplished by creating a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). Here we are supporting typical system engineer decisions regarding maintenance activity scheduling and component ageing management. This is performed in a risk-informed context where herein the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow. A challenge is that the structure of this workflow strongly depends on the decision that needs to be made, the type of data available, and the constraints that need to be considered. Current methods are designed to provide specific answers to specific problems; however, these methods might prove to be inadequate even when problem settings slightly change (e.g., different types of requirements, additional dependencies between system reliability and economics). We tackled this challenge by designing framework in a flexible and modular fashion such that the user can assemble and customize his/her own workflow that integrates SSC economic lifecycle models (e.g., maintenance and replacement costs), system reliability models, and optimization methods.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Bridging Equipment Reliability Data and Risk Informed Decisions in a Plant Operation Context

Industry equipment reliability and asset management programs are essential elements that help ensure the safe and economical operation of nuclear power plants. The effectiveness of these programs is addressed in several industry-developed and regulatory programs. The Risk-Informed Asset Management (RIAM) project is tasked to develop tools in support of the equipment reliability and asset management programs at nuclear power plants. These tools are designed to create a direct bridge between component health/lifecycle data and decision making (e.g., maintenance scheduling and project prioritization). The goal of this article is to provide a guide for specific use cases that the RIAM project is targeting. We have grouped uses cases into three main areas. The first area focuses on the analysis of equipment reliability data with a particular emphasis on condition-based data, such as test/surveillance reports and component monitoring data. The second area focuses on the integration of equipment reliability into system/plant reliability models to determine system/plant health and identify the components that are critical to maintain an operational system. Lastly, the third area manages plant resources, such as maintenance activities and replacement scheduling using optimization methods. Here the primary focus is on supporting typical system engineer decisions regarding maintenance activity scheduling and component aging management. This is performed in a risk-informed context where the term “risk” is broadly constructed to include both plant reliability and economics. This framework combines data analytics tools to analyze equipment reliability data with risk-informed methods designed to support system engineer decisions (e.g., maintenance and replacement schedules, optimal maintenance posture) in a customizable workflow.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

WISDEM® v3.4.1(Wind Plant Integrated System Design and Engineering Model) [SWR-14-05]

The Wind Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nlr.gov/wind/systems-engineering

Dykes, Katherine↗
DOE OSTI2022

Floating Wind Turbine Control Optimization

We present a framework for optimizing the control parameters of floating offshore wind turbines (FOWTs). The framework combines aeroelastic simulations with a systems engineering model and control software. In an example of the optimization framework, we minimize tower damage equivalent loading with generator speed constraints. We also study the effect of thrust-limiting control and quantify the trade off between fatigue loading and energy capture using a set of optimal controller designs. Finally, we optimize the controller of four different FOWT models and compare their dynamic responses. Additional details and other use cases for the framework are presented, which can optimize different control problems and evaluate FOWT designs.

controls↗
DOE OSTI2025

A Model Based Approach to Extract Health Information from Textual Data

In current nuclear power plants (NPPs) a large amount of condition-based data is being generated and stored to assess and monitor component health and performance. The format of this data can be either numeric (e.g., pump vibration data) or textual (e.g., condition report which assess component health). While assessing component health from numeric data can be performed with a large variety of methods, the extraction of information from textual data still remains a challenge. Natural language processing (NLP) methods are starting to be deployed in current NPPs mainly to filter out incident reports (IRs) that are not safety related by employing supervised machine learning methods. However, these methods do not really provide the quantitative information that might be contained in IRs. This paper presents an approach to extract information from textual data (e.g., from IRs, maintenance reports) that is based on NLP data analytics methods coupled with model-based system engineer (MBSE) models. NLP methods are employed to perform syntactic and semantic analyses. Syntactic analysis analyzes the grammatical structure of a sentence; such analysis includes: part of speech (POS) tagging (i.e., identification of grammatic elements of each string - e.g., nouns, verbs), named entity recognition (i.e., identification of text entities - e.g., names, dates, events), and relation extraction (e.g., coreference resolution). On the other hand, semantic analysis is designed to analyze the logic structure of a sentence. Through a specific set of rules, our methods can identify whether a sentence contains health information of a component (e.g., degraded performance, anomaly behavior) or the causal relationship between two events (i.e., a cause-effect pair). An innovative element of our approach is that semantic analysis relies on MBSE models to identify links between textual elements. MBSE are diagrams designed to represent system and component dependencies (from both a form and functional point of view). In our approach, MBSE models emulate system engineer knowledge about component/system architecture. This paper presents in detail how the integration of NLP methods and MBSE models is performed. Few analysis examples focusing on centrifugal pumps are presented.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Automatic Time Step Control to Resolve Hydromechanically Driven Fault Reactivation, Spontaneous Nucleation, and Seismic Arrest

Abstract A physical understanding of the progression from flow‐driven (quasi‐static) poromechanical deformation to dynamic fault rupture is critical to the resilient operations of several engineering systems. These processes are bridged by a progression from fault reactivation to the spontaneous nucleation of unstable sliding. Toward addressing this challenge, novel automatic time step size control methods are developed to enable accurate and efficient simulation of these dynamics and transitions from the first principles. The controllers combine local models for discretization error and Coulomb failure conditions to automatically adjust the time step size across several orders of magnitude. The methods do not require additional empirical or theoretical input and can resolve the pre‐rupture, interseismic, and seismic periods to the allowed accuracy. The computational results reveal that the proposed methods automatically capture the onset of reactivation and nucleation for homogeneous and heterogeneous fields. Hydrodynamic and structural heterogeneity lead to disparate critical nucleation sizes compared to those predicted by theory. The results highlight its potential in predicting induced seismicity in realistic subsurface engineering systems and at practical scales.

Environmental Sciences & Ecology↗
DOE OSTI2025

Tunable shear thickening, aging, and rejuvenation in suspensions of shape-memory-endowed liquid crystalline particles

The morphological features of particles, notably shape anisotropy, critically influence the rheological properties of dense suspensions, spanning both natural and engineered systems. This work explores the potential of using shape memory particles to dynamically regulate suspension fluid flow through controllable shape transformations. First, we synthesize shape-memory particles with programmable anisotropy from liquid crystal elastomers, such that the stiffness and shapes of the particles can be tuned by manipulating temperature. Our findings reveal that suspensions from such particles exhibit significant tunability in shear thickening behavior, transitioning from discontinuous shear thickening to a Newtonian-like response within a narrow temperature range of 60 ° C. This capability to modulate rheological responses in situ presents an approach for addressing processing challenges in many applications where control over flow behavior is paramount. Furthermore, we also show that suspensions composed of these anisotropic particles can undergo physical aging, and evolve into a glassy state. This state can be escaped upon activation of the shape memory effect. This reversibility underscores the potential for using such materials to engineer systems that can enter or come out of kinetic arrest by leveraging internal mechanical responses to external stimuli. The insights gained here not only broaden our understanding of the interplay between particle geometry and suspension dynamics but also pave the way for leveraging ensembles of stimuli-responsive objects to precisely control collective behaviors in many-body systems.

Science & Technology - Other Topics↗
DOE OSTI2023

Waste heat recovery system and control

A waste heat recovery (WHR) system that can be utilized in internal combustion engine systems includes at least two circuits, one having a low pressure working fluid and another having a high pressure working fluid. Each circuit can include heat exchangers to allow the working fluid to absorb heat form one or more heat source fluids associated with the engine. The system can also include an expander configured to receive the working fluid from the at least two circuits, and generating mechanical power. The system also can include a condenser, a sub cooler, and at least one working fluid pump to pump the working fluid in the at least two circuits. The cooling system also includes a controller that can receive temperature and pressure values from various locations in the WHR system and control at least the flow rates of the working fluids in the at least two circuits.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Implementing an Objectives-Driven, Risk-Informed, and Case-Assured Approach to Safety and Mission Success at NASA

NASA is developing a “Standard for Assurance of Space Flight Safety and Mission Success” that implements an objectives-driven, risk-informed, and case-assured approach to safety and mission success (S&MS) for NASA space flight programs and projects. The standard aligns with the philosophy of risk leadership that has recently been established in NASA policy to assure acceptable levels of flight crew safety and mission success risk. It is consistent with existing NASA risk management requirements and is compatible with NASA program management and systems engineering requirements. The methodology described in the standard is presented in terms of an S&MS assurance framework that is designed to allow substantial flexibility in the specific means by which programs and projects achieve acceptable mission S&MS risk. Such flexibility is necessary to accommodate the increasingly broad range of acquisition strategies employed by NASA, including commercial transportation services, as well as to accommodate the increasingly rapid evolution of space flight-related technologies and practices. A key feature of the S&MS assurance framework is the specification of S&MS success criteria for each life-cycle review (LCR). The S&MS assurance case is structured around these criteria, the satisfaction of which indicates that the program/project is adhering to the S&MS risk posture. This enables the evolving S&MS assurance case to be used as a fundamental program/project submittal at each LCR, where its inherent structure of argument, supported by evidence, directly supports the evaluation of the program/project with respect to the S&MS success criteria, and by extension, the S&MS risk posture. As such, the S&MS assurance case is integral to program/project systems engineering, risk management, and S&MS oversight activities, and provides the principal basis for S&MS risk acceptance by the Decision Authority throughout the program/project life cycle.

42 ENGINEERING↗
DOE OSTI2021

Advanced Syngas Cleanup Using Radically Engineered Modular Systems

The overall objective of this project was to address key knowledge gaps and develop modular sorbent-based warm syngas cleanup designs that will enable 1- to 5-MW REMS-based plants to be cost-competitive with large state-of-the-art commercial plants utilizing all of our abundant domestic coal reserves. We proposed to develop two potential new desulfurization process designs specifically targeted for REMS plants for combined heat and power or polygeneration from coal gasification. The first design is a modification of our commercially offered dual transport reactor design based Warm-gas Desulfurization Process (WDP) where the transport-reactor regenerator is replaced with a fluidized-bed regenerator. This design leverages the learnings obtained from our pre-commercial demonstration testing of the WDP technology for over 3,000 hours and conclusions from the lessons learned workshop. The second design is a fixed-bed process that leverages the successful composition and chemistry of our WDP sorbent to develop an effective fixed-bed sorbent formulation and fixed-bed process design. These two potential desulfurization process designs have a strong technical likelihood of success and offer the best opportunity to effectively employ design standardization, mass production and advanced manufacturing techniques to enable cost competitiveness for syngas cleanup at smaller scale.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2020

Database Management Module Framework for Dynamic Contingency Analysis and Visualization

The Dynamic Contingency Analysis Tool (DCAT) is being developed to mimic the response of generation dynamics, protection, and load components to extreme contingencies in power systems. Currently, DCAT generates a huge data set, with the analysis results stored in multiple subfolders using a great many files in different formats (power flow cases, time series, figures, spreadsheets). To help power system engineers thoroughly understand and analyze system behavior under many scenarios and contingencies, we developed a database management module (DBM) that enables future integration of DCAT with industry-grade Big Data analytical and interactive visualization platforms. In this paper, we demonstrate the DBM framework with interactive analytics and visualization for DCAT on the synthetic South Carolina 500-bus power system model using hurricane contingencies that capture possibilities for an extreme contingency. DCAT’s advanced data management and interactive visualization can help planning engineers to visually explore and analyze system behavior, all in one view.

Cascading, dynamic simulations, database managemen↗
DOE OSTI2024

WISDEM® v3.15.2 2024 (Wind-Plant Integrated System Design and Engineering Model) [SWR-14-05]

The Wind-Plant Integrated System Design and Engineering Model (WISDEM®) is a set of models for assessing overall wind plant cost of energy (COE). The models use wind turbine and plant cost and energy production as well as financial models to estimate COE and other wind plant system attributes. WISDEM® is accessed through Python, is built using OpenMDAO, and uses several sub-models that are also implemented within OpenMDAO. These sub-models can be used independently but they are required to use the overall WISDEM® turbine design capability. Please install all of the pre-requisites prior to installing WISDEM® by following the directions below. For additional information about the NWTC effort in systems engineering that supports WISDEM® development, please visit the official NREL systems engineering for wind energy website. https://www.nrel.gov/wind/systems-engineering.html

Dykes, Katherine↗
DOE OSTI2020

An Update to the National Renewable Energy Laboratory Baseline Wind Turbine Controller

The National Renewable Energy Laboratory's 5-MW wind turbine model is well established as an industry standard and is often used as a comparison model, or a model on which to build upon. Though effective, the legacy controller for the 5-MW wind turbine uses a simple algorithm that is not up to date with many industry standards. Additionally, as the research community has advanced into fast-paced development cycles, as systems engineering tools such as Wind-Plant Integrated System Design & Engineering Model (WISDEM ®) [1] are employed, and as a greater focus on controls co-design practices is encouraged, demand for a generic wind turbine controller has arisen. This work presents updates for the NREL 5-MW controller to a more modern control architecture, and establishes a generic tuning framework that can be easily adapted to various wind turbines. Based on initial results, the updated generic controller eases the automatic tuning process while maintaining or improving the performance of the legacy NREL 5-MW controller.

17 WIND ENERGY↗
DOE OSTI2021

Performance Evaluation of Engineered Geothermal Systems Using Discrete Fracture Network Simulations

Electrical power production from geothermal energy has a solid record of success for permeable reservoirs such as The Geysers in northern California and geothermal systems in Iceland and New Zealand, among other places. Such permeable reservoirs, however, represent only a small fraction of the available heat energy in the earth’s shallow crust. Most of the available energy resides in rocks with insufficient permeability and storage to produce commercial volumes of heated fluids.

15 GEOTHERMAL ENERGY↗