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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 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The Nuclear System-of-Systems Capabilities Analytic Process

This dissertation discusses the impetus for, development of, and initial demonstration of NuSCAPTM: the Nuclear System-of-Systems Capabilities Analytic Process TM . NuSCAP is an approach executed via a Python® application that enables capabilities-based vulnerability analyses of military systems of systems (SOS) exposed to prompt nuclear weapon effects. The NuSCAP application calls on industry-standard, fast-running nuclear weapon effects tools and the Monte Carlo N-Particle®1 (MCNP®) code to evaluate the impact of nuclear weapon environments on the military capabilities of a complex and networked SOS.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
NASA NTRS1996

A bioreactor system for the nitrogen loop in a Controlled Ecological Life Support System

As space missions become longer in duration, the need to recycle waste into useful compounds rises dramatically. This problem can be addressed by the development of Controlled Ecological Life Support Systems (CELSS) (i.e., Engineered Closed/Controlled Eco-Systems (ECCES)), consisting of human and plant modules. One of the waste streams leaving the human module is urine. In addition to the reclamation of water from urine, recovery of the nitrogen is important because it is an essential nutrient for the plant module. A 3-step biological process for the recycling of nitrogenous waste (urea) is proposed. A packed-bed bioreactor system for this purpose was modeled, and the issues of reaction step segregation, reactor type and volume, support particle size, and pressure drop were addressed. Based on minimization of volume, a bioreactor system consisting of a plug flow immobilized urease reactor, a completely mixed flow immobilized cell reactor to convert ammonia to nitrite, and a plug flow immobilized cell reactor to produce nitrate from nitrite is recommended. It is apparent that this 3-step bioprocess meets the requirements for space applications.

NASA Discipline Number 61-10↗
NASA NTRSDate not supplied

A Model-Based Systems Engineering Evaluation of the Evolution to an In-Time Aviation Safety Management System

In 2018, as result of a recommendation from the National Academies, NASA began to prototype an In-Time Aviation Safety Management System (IASMS). The purpose of the IASMS is to enable innovative aviation operations and greater heterogeneity of the overall National Airspace (NAS) by automating much of the safety monitoring, assessment, and risk and hazard mitigation function present in today’s Safety Management Systems (SMS). NASA has worked together with early industry collaborators to understand how such a system might work and has published several early Concepts of Operation (ConOps) and other technical memoranda that illustrate the primary considerations for selected aviation domains. The shift from an SMS to an IASMS is predicated on several assumptions, including: 1.) automating safety functions will decrease the amount of time necessary for risk and hazard identification and analysis, making it more likely that safety concerns are understood ‘in-time’ to mitigate them, and 2.) an IASMS will allow easier tailoring of safety management processes to the particular risks and hazards inherent to that aviation operation. In this paper, we begin to validate these assumptions through the use of Model-Based Systems Engineering (MBSE).

IASMS↗
DOE OSTI2017

Control Systems for a Dynamic Multi-Physics Model of a Nuclear Hybrid Energy System

A Nuclear Hybrid Energy System (NHES) uses a nuclear reactor as the basic power generation unit, and the power generated is used by multiple customers as either thermal power, electrical power, or both. The definition and architecture of a particular NHES can be adapted based on the needs and opportunities of different local markets. For example, locations in need of potable water may be best served by coupling a desalination plant to the NHES. Similarly, a location near oil refineries may have a need for emission-free hydrogen production. Using the flexible, multi-domain capabilities of Modelica, Argonne National Laboratory, Idaho National Laboratory, and Oak Ridge National Laboratory are investigating the dynamics (e.g., thermal hydraulics and electrical generation/consumption) and cost of a hybrid system. This paper examines the NHES work underway, emphasizing the control system developed for individual subsystems and the overall supervisory control system.

control system↗
DOE OSTI2024

Development of Supervisory Control System for Thermal Energy Distribution System

The integrated energy system (IES) refers to the combination of nuclear energy generation with other energy sources to enable the efficiency and reliability of power generations. To create technologically viable and economically competitive systems, supervisory control strategies are critical for optimizing performance and ensuring stability across different energy generation, transportation, and utilization. This work focuses on the control strategies for the thermal energy distribution system (TEDS), which is a cornerstone of the Dynamic Energy Transport and Integration Laboratory at Idaho National Laboratory. TEDS currently relies on operators to coordinate across different components to manage energy storage and ensure efficiency. This work demonstrates the use of model predictive control (MPC) with surrogate models in determining optimal setpoints for major TEDS components. The capability of MPC-based supervisory control system is evaluated by autonomously matching the power outputs from a Dymola-based TEDS with target heat demands.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2016

Toward more realistic projections of soil carbon dynamics by Earth system models

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool-and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. Furthermore, we recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

Software and Hardware Systems in the Safety Control Systems of Nuclear Power Plants

Fundamentally new software and hardware systems for lower level automation in the safety monitoring and control systems of nuclear power plants are examined. More than a hundred software-hardware systems employing software and hardware from different manufacturers have been developed and introduced in this area. Design and functional solutions based on specific software-hardware systems are presented and comparative data on the apparatus and the use of the diversity principle are discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2017

A suite of benchmark and challenge problems for enhanced geothermal systems

A diverse suite of numerical simulators is currently being applied to predict or understand the performance of enhanced geothermal systems (EGS). To build confidence and identify critical development needs for these analytical tools, the United States Department of Energy, Geothermal Technologies Office sponsored a Code Comparison Study (GTO-CCS), with participants from universities, industry, and national laboratories. A principal objective for the study was to create a community forum for improvement and verification of numerical simulators for EGS modeling. Teams participating in the study were those representing U.S. national laboratories, universities, and industries, and each team brought unique numerical simulation capabilities to bear on the problems. Two classes of problems were developed during the study, benchmark problems and challenge problems. The benchmark problems were structured to test the ability of the collection of numerical simulators to solve various combinations of coupled thermal, hydrologic, geomechanical, and geochemical processes. This class of problems was strictly defined in terms of properties, driving forces, initial conditions, and boundary conditions. The challenge problems were based on the enhanced geothermal systems research conducted at Fenton Hill, near Los Alamos, New Mexico, between 1974 and 1995. The problems involved two phases of research, stimulation, development, and circulation in two separate reservoirs. The challenge problems had specific questions to be answered via numerical simulation in three topical areas: (1) reservoir creation/stimulation, (2) reactive and passive transport, and (3) thermal recovery. Whereas the benchmark class of problems were designed to test capabilities for modeling coupled processes under strictly specified conditions, the stated objective for the challenge class of problems was to demonstrate what new understanding of the Fenton Hill experiments could be realized via the application of modern numerical simulation tools by recognized expert practitioners. Lastly, we present the suite of benchmark and challenge problems developed for the GTO-CCS, providing problem descriptions and sample solutions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Periodically driven ergodic and many-body localized quantum systems

We study dynamics of isolated quantum many-body systems whose Hamiltonian is switched between two different operators periodically in time. The eigenvalue problem of the associated Floquet operator maps onto an effective hopping problem. Using the effective model, we establish conditions on the spectral properties of the two Hamiltonians for the system to localize in energy space. We find that ergodic systems always delocalize in energy space and heat up to infinite temperature, for both local and global driving. In contrast, many-body localized systems with quenched disorder remain localized at finite energy. We support our conclusions by numerical simulations of disordered spin chains. We argue that our results hold for general driving protocols, and discuss their experimental implications.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2015

Design guidelines for avoiding thermo-acoustic oscillations in helium piping systems

Thermo-acoustic oscillations are a commonly observed phenomenon in helium cryogenic systems, especially in tubes connecting hot and cold areas. The open ends of these tubes are connected to the lower temperature (typically at 4.2 K), and the closed ends of these tubes are connected to the high temperature (300K). Cryogenic instrumentation installations provide ideal conditions for these oscillations to occur due to the steep temperature gradient along the tubing. These oscillations create errors in measurements as well as an undesirable heat load to the system. The work presented here develops engineering guidelines to design oscillation-free helium piping. This work also studies the effect of different piping inserts and shows how the proper geometrical combinations have to be chosen to avoid thermo-oscillations. The effect of an 80 K intercept is also studied and shows that thermo-oscillations can be dampened by placing the intercept at an appropriate location.

43 PARTICLE ACCELERATORS↗
DOE OSTI2014

Theory and Implementation of Nuclear Safety System Codes - Part II: System Code Closure Relations, Validation, and Limitations

This is Part II of two articles describing the details of thermal-hydraulic sys- tem codes. In this second part of the article series, the system code closure relationships (used to model thermal and mechanical non-equilibrium and the coupling of the phases) for the governing equations are discussed and evaluated. These include several thermal and hydraulic models, such as heat transfer coefficients for various flow regimes, two phase pressure correlations, two phase friction correlations, drag coefficients and interfacial models be- tween the fields. These models are often developed from experimental data. The experiment conditions should be understood to evaluate the efficacy of the closure models. Code verification and validation, including Separate Effects Tests (SETs) and Integral effects tests (IETs) is also assessed. It can be shown from the assessments that the test cases cover a significant section of the system code capabilities, but some of the more advanced reactor designs will push the limits of validation for the codes. Lastly, the limitations of the codes are discussed by considering next generation power plants, such as Small Modular Reactors (SMRs), analyz- ing not only existing nuclear power plants, but also next generation nuclear power plants. The nuclear industry is developing new, innovative reactor designs, such as Small Modular Reactors (SMRs), High-Temperature Gas-cooled Reactors (HTGRs) and others. Sub-types of these reactor designs utilize pebbles, prismatic graphite moderators, helical steam generators, in- novative fuel types, and many other design features that may not be fully analyzed by current system codes. This second part completes the series on the comparison and evaluation of the selected reactor system codes by discussing the closure relations, val- idation and limitations. These two articles indicate areas where the models can be improved to adequately address issues with new reactor design and development.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Reinforcement learning for adaptive maintenance policy optimization under imperfect knowledge of the system degradation model and partial observability of system states

Maintenance policy optimization usually is faced with challenges that arise from an imperfect knowledge of system degradation models and from the partial observability of system degradation states. Here, this paper proposes a reinforcement learning method to address these two challenges for a class of maintenance problems with Markov degradation processes. The reinforcement learning approach consists of a learning component and a planning component. Using sequentially collected observations, at each step of decision-making the learning component improves the knowledge of system degradation in terms of the probability distributions of the transition rates based on sequential Bayesian inference. Using the updated transition rates, at each step of decision-making the maintenance policy optimization problem is then formulated as a partially observable Markov decision problem, and the planning component computes the optimal maintenance policy that maximizes the expected cumulative reward. The proposed method is illustrated using a numerical example with repair and inspection maintenance actions. The result shows that as more observations are collected, the learning component progressively learns the true system degradation process, and the planning component adjusts the optimal maintenance policy accordingly as well, which leads to increased reward.

42 ENGINEERING↗