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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Encoding of symbols for a computer interconnect based on frequency of symbol values

Data are serially communicated over an interconnect between an encoder and a decoder. The encoder includes a first training unit to count a frequency of symbol values in symbol blocks of a set of N number of symbol blocks in an epoch. A circular shift unit of the encoder stores a set of most-recently-used (MRU) amplitude values. An XOR unit is coupled to the first training unit and the first circular shift unit as inputs and to the interconnect as output. A transmitter is coupled to the encoder XOR unit and the interconnect and thereby contemporaneously sends symbols and trains on the symbols. In a system, a device includes a receiver and decoder that receive, from the encoder, symbols over the interconnect. The decoder includes its own training unit for decoding the transmitted symbols.

SeyedzadehDelcheh, SeyedMohammad↗
DOE OSTI2025

The Impact of Cultural Values and Organizational Processes on Nuclear Security Operations

Human performance is a pivotal factor in the design, testing, maintenance, and operation of security systems. The effectiveness of these systems relies not only on the capabilities, limitations, motives, and attitudes of the individuals involved, but also on the quality of training, instructional content, and evaluation methods provided. To uphold security standards, seamless integration between technologies and operators necessitates reliable human input. In security operations, human errors, often attributed to blame, sanctions, low motivation, individual accountability, or complacency, are primary causes of system failures. Complacency, characterized by a false sense of security, reflects a lack of awareness of potential threats and is a significant contributing factor to lapses in security. Security incidents arise from various factors, many extend beyond individual control, highlighting the need for a holistic approach to human performance that integrates organizational processes and team collaboration. Historically, errors have been attributed to individual moral or cognitive failures. However, insights from Operational Experiences (OEs) suggest that organizational processes weakness and deficiencies in nuclear cultural values contribute more significantly to security failures than individual mistakes. This paper consolidates lessons learned from diverse international nuclear security cultures and aims to highlight the importance of security culture in shaping global perspectives on nuclear security. It underscores the role of cultural values in shaping nuclear security practices and enhancing the resilience of security systems in the nuclear sector.

Zineddin, Dr. Z. [ORNL] (ORCID:0009000848740725)↗
DOE OSTI2019

Estimating the Impact of Residual Value for Electricity Generation Plants on Capital Recovery, Levelized Cost of Energy, and Cost to Consumers

There is often a benefit to continue operating electricity generating assets after their initial contracts expire. This report discusses these benefits and associated risks, using data and illustrative calculations. The key findings are: the realized operational lives of generation technologies before retirement are typically much longer than typical measures of economic lives. The cost impact of a life extension can be comparable to the impact of other factors considered for generation investment decisions, and suggests that R&D and commercial efforts to extend generator life may be valuable. Refurbishment has a useful and economic role, but the option is often neglected during initial investment. Estimating follow-on value at the time of the original investment is complex and often neglected, but may be valuable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Randomized algorithms for generalized singular value decomposition with application to sensitivity analysis

The generalized singular value decomposition (GSVD) is a valuable tool that has many applications in computational science. However, computing the GSVD for large-scale problems is challenging. Motivated by applications in hyper-differential sensitivity analysis (HDSA), in this work we propose new randomized algorithms for computing the GSVD which use randomized subspace iteration and weighted QR factorization. Detailed error analysis is given which provides insight into the accuracy of the algorithms and the choice of the algorithmic parameters. We demonstrate the performance of our algorithms on test matrices and a large-scale model problem where HDSA is used to study subsurface flow.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Continuous Dependence on Translations of the Independent Variable for Solutions of Boundary-Value Problems for Differential-Difference Equations

We consider boundary-value problems for differential-difference operators with perturbations in translations of the independent variable. We prove that the family of differential-difference operators is positive definite uniformly with respect to translations of the independent variable. Solutions of such problems depend continuously on these translations. We consider the coercivity problem for differential-difference operators with incommensurable translations of the independent variable and study the approximation of such operators by rational operators.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Model Elliptic Boundary-Value Problems for Pseudodifferential Operators in Canonical Nonsmooth Domains

We consider a simplest elliptic pseudodifferential equation in a multi-dimensional cone (multi-dimensional angle) and describe all possible structures of its solutions related to the wave factorization of the elliptic symbol. Depending on the index of wave factorization, we consider various statements of well-posed boundary-value problems. The existence of solutions is studied in Sobolev–Slobodetskii spaces.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Initial-Boundary Value Problem for the Nonstationary Radiative Transfer Equation with Diffuse Reflection and Refraction Conditions

We consider the initial-boundary value problem for the nonstationary radiative transfer equation in a system of semitransparent bodies with the conditions of diffuse reflection and refraction of radiation. We establish the unique solvability of the problem with boundary and initial data in the complete scale of Lebesgue spaces. We obtain estimates for solutions.

42 ENGINEERING↗
DOE OSTI2019

Analysis of the Spectral Stability of the Generalized Runge–Kutta Methods Applied to Initial-Boundary-Value Problems for Equations of the Parabolic Type. II. Implicit Methods

We consider specific realizations of different implicit generalized Runge–Kutta methods as applied to the numerical integration with respect to time of initial-boundary-value problems for the second-order parabolic equations and investigate their spectral stability. It is shown that all implicit generalized Runge–Kutta methods are unconditionally spectrally stable but some of them have the conditional property of monotonicity of the numerical solution with respect to time. The functions of spectral stability of the implicit generalized Runge–Kutta methods are rational. We compare the analytic solution of the nonstationary one-dimensional problem of heat conduction with the numerical solutions of this problem obtained by different implicit generalized Runge–Kutta methods. It is shown that, in this case, the application of the one-stage Radau methods with subsequent discretization of the problem with respect to the space variable leads to the classical forward finite difference scheme (Laasonen scheme), whereas the use of the one-stage Gauss–Legendre method leads to a six-point symmetric scheme (Crank–Nicolson scheme). It is shown that diagonally implicit generalized Nørsett and Burrage methods are realized in almost the same way as the one-stage Radau and Gauss–Legendre methods but their accuracy in the time step is 10–1000 times higher. On the basis of comparison of the numerical and analytic solutions, we conclude that, in order to get practically suitable numerical solutions without any restrictions on the time step, it is reasonable to use one- and three-stage generalized Radau methods or two- and four-stage Lobatto IIIC methods. All other explicit and implicit generalized Runge–Kutta methods require certain restrictions imposed on the time step.

42 ENGINEERING↗
DOE OSTI2021

Chapter 2: Global Value Chain and Manufacturing Analysis on Geothermal Power Plant Turbines

The global geothermal power market has shown significant growth since the last decade and is expected to reach a total installed capacity of 18.4 gigawatts electric (GWe) by the end of 2021 (GEA, 2016). The global geothermal power plant turbine market is dominated by a small number of manufacturers. Between 2005 and 2015, 82% of the geothermal steam turbines were manufactured in Japan, and 74% of the geothermal binary cycle turboexpanders were manufactured in Israel. During this period, the United States played an important role in the global trade flow of fully assembled turbine units and turbine parts, with a high volume of imports and exports. Another significant growth area was in Italian turbine/turboexpander manufacturers, who have increased their market share in the last couple of years. One other important change in the manufacturing market was in Turkey, where the bonus on feed-in-tariff (FIT) for domestic hardware components boosted the national manufacturing sector between 2010 and 2020. When planning geothermal power projects, developers customize their power plant size to fit the available geothermal resource capacity. The turbine is designed and sized to optimize the efficiency and utilization of resource and revenue production. The rest of the power plant components such as heat exchangers (HX), water-cooled cooling towers (WCCT), or air-cooled condensers (ACC) are then chosen to complement the turbine size and design. These one-off manufacturing custom design turbines have relatively higher manufacturing set-up costs, longer lead times, and higher capital costs than the standard design turbines manufactured in larger volumes. However, turbines produced in standard increments and in larger manufacturing volumes could result in lower costs per turbine, but potentially lower efficiency. Based on pipeline projects and resource assessments, there is significant potential value in creating standard turbine sizes that could offer an economic advantage, as is done for modular microturbines.

40 EE - Geothermal Technologies Office (EE-4G)↗
DOE OSTI2020

Singular value decomposition of adjoint flux distributions for Monte Carlo variance reduction

Monte Carlo (MC) shielding calculations often use weight windows (WWs) and biased sources formed from a deterministic estimate of the adjoint flux to improve the convergence rate of tallies. This requires a significant amount of computer memory, which can limit the memory available for high-resolution tally output. A new method is proposed for reducing these memory requirements by using singular value decomposition (SVD) in linear or logarithmic space to approximate the adjoint flux. This method’s performance is evaluated using the Shift and Denovo codes for streaming and diffusion base case problems, followed by problems using the Westinghouse AP1000 and the Joint European Torus. The log SVD reduced WW memory requirements by an order of magnitude in all cases without a significant performance penalty. Additionally, the linear SVD reduced biased source memory requirements by an order of magnitude, but further investigation is needed to account for observed limitations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2019

Holistic modeling framework of demand response considering multiti-mescale uncertainties for capacity value estimation

Demand response (DR) is regarded as an effective tool to mitigate the operational uncertainties and enhance the reliability of power supply in smart grids. However, with the time-varying attribute, to what extent DR could be committed is a major concern for utilities. This paper proposes a new approach to assess the capacity value (CV) of DR with a methodological framework developed for the uncertainty modeling of DR. The novelty of this framework is its inclusion of both physical and human-related analyses in DR programs, which allows the characterization of DR variability to be accurate for the CV estimation. To achieve this, the demand-side activities in DR are disaggregated into several modules as load usage, contract selection and actual performance. Based on their intrinsic properties, different parametric models are proposed to represent the impact of each technical/social factor on the availability of DR. The parameters of these models are determined using learning based algorithms to adapt to various behavior patterns of consumers. The outputs of the framework will serve as the quantifiers of DR capability and are integrated into reliability-based CV evaluation. The results of case studies verify the effectiveness of the proposed methodology.

Capacity value↗
DOE OSTI2019

Property values associated with the failure of individual links in a system with multiple weak and strong links

Representations are developed and illustrated for the distribution of link property values at the time of link failure in the presence of aleatory uncertainty in link properties. The following topics are covered: (i) defining properties for weak links and strong links, (ii) cumulative distribution functions (CDFs) for link failure time, (iii) integral-based derivation of CDFs for link property at time of link failure, (iv) sampling-based approximation of CDFs for link property at time of link failure, (v) verification of integral-based and sampling-based determinations of CDFs for link property at time of link failure, (vi) distributions of link properties conditional on time of link failure, and (vii) equivalence of two different integral-based derivations of CDFs for link property at time of link failure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Estimating value of information for heliostat washing operations at solar thermal plants

Concentrating solar power (CSP) plants depend on thousands of heliostats whose reflectance declines as dust accumulates. Operators routinely measure reflectance to estimate soiling and, in turn, inform cleaning schedules, but the value of collecting more frequent or more accurate data has not been formally quantified. This study introduces a Monte Carlo discrete event simulation framework that integrates stochastic models of soiling, weather, and measurement error with a dynamic cleaning dispatch policy to estimate annual energy production and operations costs. Applied to two representative central-receiver field configurations, the results show that both the frequency and accuracy of reflectance measurements can meaningfully impact plant performance. In both case studies, reducing measurement intervals yields significant returns, with the energy gains greatly exceeding the cost of more frequent data collection. The simulation framework serves as a decision-support tool for CSP operators, allowing them to input site-specific soiling conditions, measurement accuracy, and survey frequency to evaluate the tradeoffs between data collection cost and energy recovery, and to identify measurement strategies that maximize plant profit.

14 SOLAR ENERGY↗
DOE OSTI2021

Do automated vehicle (AV) enthusiasts value travel time differently from cautious travelers? an exploration of travelers’ attitudes towards AV

The anticipation of automated vehicles (AV) has resulted in diverse research topics, including understanding the adoption and usage of this emerging mode. Using attitudinal indicators, this paper identifies prevalent types of attitudes towards AV. It then explores the variation of those attitudes across different demographic groups and quantifies the influence of these attitudes on the preference for AV. The paper uses stated preference survey data collected among respondents of Chicago in 2019. The exploratory factor analysis of the attitudinal indicators identifies four factors, namely 'Cautious Travelers', 'Hedonists', 'Utilitarians', and 'Safety-First'. Next, the paper develops an integrated choice and latent variable model to test the influence of these four types of attitudes on the preference for AV. Finally, the results indicate that the cautious travelers associate higher Value of Travel Time (VOTT) to AV and enthusiasts associate lower VOTT to AV than a base model without such attitudes.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

Value Gradient Learning Approach in Power and Frequency Regulation of Grid-Connected Synchronverters

In this paper, a neural network adaptive critic design (ACD) method based on value gradient learning (VGL) is used to optimally control a grid-connected synchronverter. The main drawback of the traditional synchronverters is their infeasibility to face non-inductive grids. To be able to implement a synchronverter technique in any impedance angle, a neural network-based adaptive controller is used. The advantage of adaptive dynamic programing is its ability to adjust itself when it faces changes and uncertainties in the power system. The proposed VGL consists of two subnetworks: the critic network and the action network. The action network is trained during the operation, and the critic network can be pretrained offline or can be simultaneously trained with the action network. To compare the effectiveness of the traditional synchronverter to the VGL-based synchronverter, the simulation results are provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Synchrophasor Data Compression Under Disturbance Conditions via Cross-Entropy-Based Singular Value Decomposition

The increasing deployment of phasor measurement units and the advances of their reporting rates are challenging the present data centers in terms of storing and analyzing large-volume data. Under power system disturbance conditions, it is difficult to retain critical information while compressing the synchrophasor data effectively. This article combines the cross entropy and the singular value decomposition, proposing a novel model to compress the synchrophasor data to an extremely small size yet keep superior accuracy. The proposed model is extensively tested and compared with the state-of-the-art algorithms using the simulated and the FNET/GridEye field-collected data. The result indicates that the proposed algorithm has superior performance in compressing the data while retaining critical information under disturbance conditions.

42 ENGINEERING↗