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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 109 records · Page 6

The Effect of Stochastic Perturbation of Fuel Distribution on the Criticality of a One Speed Reactor and the Development of Multi-Material Multinomial Line Statistics

The effect of random fuel redistribution on the eigenvalue of a one-speed reactor is investigated. An ensemble of such reactors that are identical to a homogeneous reference critical reactor except for the fissile isotope density distribution is constructed such that it meets a set of well-posed redistribution requirements. The average eigenvalue, , is evaluated when the total fissile loading per ensemble element, or realization, is conserved. The perturbation is proven to increase the reactor criticality on average when it is uniformly distributed. The various causes of the change in reactivity, and their relative effects are identified and ranked. From this, a path towards identifying the causes. and relative effects of reactivity fluctuations for the energy dependent problem is pointed to. The perturbation method of using multinomial distributions for representing the perturbed reactor is developed. This method has some advantages that can be of use in other stochastic problems. Finally, some of the features of this perturbation problem are related to other techniques that have been used for addressing similar problems.

Jahshan, S. N.↗

Probabalistic Risk Analysis and Thermal Margin Process for an Inflatable Aeroshell

Uncertainties always exist in atmospheric entry aeroheating environments and the thermal response of thermal protection system (TPS) material. These uncertainties are mitigated in the design by ap-plying margin and factors of safety to the TPS. Entry vehicle TPS is often conservatively over-sized for the heat loads that are experienced along the entry trajectory by stacking worst-case scenarios together. Additionally, the current TPS design and margin process used by NASA offers very little insight into the risk of over-temperature during flight and the reliability of the heat shield performance [1,3]. A probabilistic margin process can be used to calculate the amount of TPS margin necessary to survive a given entry heat load at a specified level of risk [2,3,4]. The vehicle’s initial entry state (entry velocity, flight path angle, and entry mass) determines the expected atmospheric entry environmental conditions and resulting heat load that the entry vehicle will experience. If there is flexibility in the entry state, then this process can be used to select an appropriate combination of entry state parameters and TPS size to target a desired reentry reliability. This probabilistic margin process allows engineers to make informed aeroshell design, entry-trajectory design, and TPS performance risk trades while preventing excessive TPS margin from being applied. The probabilistic TPS margin process has been performed to determine TPS thickness and entry heating constraints given an acceptable risk level for the Low Earth Orbit Flight Experiment of an Inflatable Decelerator (LOFTID) flight project. The process is used in a manner to size the entry heat load for a given flexible TPS (FTPS) thickness so that it meets project reliability standards while allowing the FTPS and the underlying inflatable structure (IS) to be pushed to adequately high temperatures. Since the LOFTID project is an experimental flight demonstration, it is de-sired to drive the FTPS and IS to temperatures that cover a large range of their thermal response models’ applicability. This will allow the thermal response models to be better improved and validated post-flight using LOFTID’s extensive instrumentation embedded within the aeroshell. The presentation demonstrates how uncertainty analysis is carried out using an end-to-end Monte Carlo process where three separate Monte Carlo simulations are run in sequence. The first Monte Carlo simulation operates on the entry trajectory model to generate trajectory parameter dispersions that are fed into the second Monte Carlo simulation. The second Monte Carlo simulation operates on the aerothermodynamics model to generate aeroheating parameter dispersions that are fed into the third Monte Carlo simulation. The third Monte Carlo simulation operates on the FTPS material thermal response model to generate the final FTPS/IS thermal response dispersions. The end-to-end Monte Carlo simulation propagates the uncertainties of each model into the next to quantify the resulting uncertainty of the FTPS/IS thermal response. The fractional contributions of the uncertain parameters in the trajectory, aerothermal, and thermal response models to the variance in the FTPS/IS thermal response is determined as a byproduct of the Monte Carlo analysis. The structural uncertainty of the FTPS thermal response model is evaluated by flight relevant ground testing and model error analysis using test measurements. This probabilistic TPS margin process had never been applied to an entry vehicle and it is one of the LOFTID project’s goals to demonstrate its merits.

Steven A. Tobin↗

Probabilistic Assessment of Structural Integrity

A probability-based approach, combining deterministic and probabilistic methods, was developed for analyzing building and component failures, which are especially crucial for complex structures like nuclear power plants. This method links finite element and probabilistic software to assess structural integrity under static and dynamic loads. This study uses NEPTUNE software, which is validated, for a deterministic transient analysis and ProFES software for probabilistic models. In a case study, deterministic analyses with varied random variables were transferred to ProFES for probabilistic analyses of piping failure and wall damage. A Monte Carlo Simulation, First-Order Reliability Method, and combined methods were employed for probabilistic analyses under severe transient loading, focusing on a postulated accident at the Ignalina Nuclear Power Plant. The study considered uncertainties in material properties, component geometry, and loads. The results showed the Monte Carlo Simulation method to be conservative for high failure probabilities but less so for low probabilities. The Response Surface/Monte Carlo Simulation method explored the impact load–failure probability relationship. Given the uncertainties in material properties and loads in complex structures, a deterministic analysis alone is insufficient. Probabilistic analysis is imperative for extreme loading events and credible structural safety evaluations.

Mathematics↗

Seasonal Cost-Benefit Analysis of Automated Distribution Feeder Upgrades with Advanced Mitigation Technologies

The increasing deployment of distributed solar photovoltaics (DPV) to meet clean energy goals can trigger adverse grid operation issues, such as voltage excursions and the violation of thermal loading constraints of the power delivery elements (e.g., lines and transformers) on the evolving electricity infrastructure. Such integration issues would require distribution upgrades with associated costs to mitigate them and to maintain reliable and resilient grid operating conditions. Traditional distribution network upgrade approaches use a specific single snapshot analysis that is overly conservative. This study considers a multi-time point analysis to capture both moderate (probable bounds) and extreme grid operating conditions using time points such as minimum load with minimum photovoltaics (PV), maximum load with maximum PV, maximum load with minimum PV, and minimum load with maximum PV. Further, this study investigates seasonal variation impacts and associated distribution upgrade costs for a spring season case (March, representing a low load and high PV scenario) and a summer case (July, representing a high load and high PV scenario). Such seasonal analysis will allow system operators to characterize upgrade requirements and associated costs across various periods. Because the spatial distribution of DPV can impact upgrade and associated costs, this study investigates three common DPV deployment scenarios - randomly deployed, close to the substation, and far from the substation - at different penetration levels. Apart from spatial distribution impacts, this project evaluates the techno-economic impacts of the nodal photovoltaic penetration factor (NPPF) for generating the various DPV deployment scenarios at increasing penetration levels. This project investigates the impact of varying nodal PV-to-load ratios using conservative and extreme NPPF values of 3 and 10, respectively. This study investigates the deployment of traditional infrastructure upgrade strategies, such as installing new voltage regulating equipment, transformers and lines replacements, and the activation of advanced inverter functionality (e.g., autonomous volt/VAR) in expanding PV hosting capacity. Existing DPV systems are assumed to operate with the legacy unity power factor, and we considered the possibility of retrofitting such systems with the activation of volt/VAR control as integration standards and regulations continue to evolve to allow such functions. The cost-benefit analysis metrics used in study include distribution upgrade costs, average cost per watt of the upgrade cost, average marginal cost per watt of the upgrade cost, and power losses.

14 SOLAR ENERGY↗

A Comparison of PV Resource Modeling for Sizing Microgrid Components

Microgrid systems are being deployed with increased frequency to meet critical building loads during unplanned power outages. Determining the appropriate type and size of components that make up a microgrid can greatly affect its ability to meet this need. This paper presents a new tool to appropriately size PV, battery, and generator capacities to meet all site loads, given a resilience goal. It uses a statistical model to simulate microgrid behavior under a large range of solar resource conditions, providing resilience planners with confidence that critical loads will be met even under extreme weather conditions. We compare this model with one that uses typical weather data for sizing microgrids, and quantify the resilience effects of using these different methods. Our method produces more conservative generator capacities and fuel requirements in an outage, predicting up to 30% more fuel required in the most extreme case. Microgrid systems that are designed using more conservative estimates are more likely to continue to serve load during emergency outages under a large range of conditions.

Newman, Sarah F.↗

Lessons Learned from Recent Space Flight Assessments

This paper highlights four space flight assessments, each with an important lesson. The first assessment points to the challenge of material substitution for weight saving. Space Shuttle’s external tank stringers were changed from Al 2024 to Al 2090 without comprehensive analysis. Lack of understanding the low Short-Transverse (S-T) strength associated with Al 2090 led to widespread cracking. The second assessment addresses the failure to understand that time-dependent relationships and loading interactions of multiple disciplines can lead to non-conservative results. An aerodynamic test article of the Orion Multi-Purpose Crew Vehicle (MPCV) Launch Abort System (LAS) was analyzed for worst-case single discipline loads, showing positive structural margins. When disciplines were combined with time dependent loading, the analysis resulted in negative margins. The third assessment highlights the pitfalls of putting blind trust in historical architecture. The MPCV re-entry heat shield adopted the Apollo design approach despite fundamental differences between the two designs (e.g., the underlying substructure design, material differences, scale, and geometry). Manufacturing resulted in cracking along seams of the cured MPCV heat shield and produced lower mechanical properties of the Avcoat witness panels. Subsequently, the design was changed to a block architecture, which introduced unperceived technical, cost, and schedule risk. The fourth assessment shows how the lack of a comprehensive investigation of design modifications and inappropriate Finite Element Analyses (FEA) can lead to trouble. A mass reduction campaign eliminated highly critical internal struts on the ISS Node-1 pressurized module based on inadequate and uncorrelated FEA. High strains were noted and ignored as a modeling aberration. A system level high fidelity FEA discovered large plastic strains in the gussets of all four radial ports. These findings initiated a full-scale test campaign, new test correlated assembly-level FEA, and significant design modifications.

James P Smith↗

Managing Army Plug Load Equipment Energy Use: Office Equipment

Office equipment covers a large and diverse group of plug load devices. Policies focused on equipment purchase, power management, and usage limitations can save the Army more than 10 million kWh and $620K per year within just four building categories. This represents a top opportunity for energy- and cost-savings identified by a recent Army plug load study.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Application of path-independent integrals to elevated temperature crack growth

The applicability of the J-integral in elasto-plastic fracture mechanics is limited to isothermal, monotonic loading conditions from the theoretical viewpoint, while in many applications, for instance gas turbine engines, crack growth occurs in the presence of cyclic inelastic loading, thermomechanical loading and temperature gradients. A number of path-independent (P-I) integrals have been proposed which do not have the restrictions of the J-integral. A review indicates that four of these integrals, although they are not the classical conservation integrals, are path-independent under these complex loading conditions. This paper describes a combined analytical and experimental effort to evaluate the ability of these four P-I integrals to correlate the crack growth data of Alloy 718 at elevated temperatures. Results for uniform temperature, 538 C, cases indicate that all these integrals are capable of correlating the crack growth data over a wide range of cyclic plasticity.

Kim, K. S.↗

OPFLearnData: Dataset for Learning AC Optimal Power Flow

The datasets are resulting from OPFLearn.jl, a Julia package for creating AC OPF datasets. The package was developed to provide researchers with a standardized way to efficiently create AC OPF datasets that are representative of more of the AC OPF feasible load space compared to typical dataset creation methods. The OPFLearn dataset creation method uses a relaxed AC OPF formulation to reduce the volume of the unclassified input space throughout the dataset creation process. The dataset contains load profiles and their respective optimal primal and dual solutions. Load samples are processed using AC OPF formulations from PowerModels.jl. More information on the dataset creation method can be found in our publication, "OPF-Learn: An Open-Source Framework for Creating Representative AC Optimal Power Flow Datasets" and in the package website: https://github.com/NREL/OPFLearn.jl.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A Data-driven Approach for Predicting Nepheline Crystallization in High-Level Waste Glasses

High-level waste (HLW) glasses with high aluminum content are prone to nepheline crystallization during the slow canister cooling that is experienced during large-scale production. Due to its detrimental effects on glass durability, nepheline precipitation must be avoided; however, developing robust, predictive models for nepheline crystallization behavior in HLW glasses is difficult due to their compositional complexity. Using overly conservative constraints to predict nepheline formation can limit the waste loading to lower than the achievable capacity. In this study, a robust data-driven model using five compositional features has been developed to predict nepheline formation. The analysis of the model and the data show that there is an overlap, instead of a distinct compositional boundary, between glasses that form and do not form nepheline. As a result, the model’s predictive accuracy is not the same throughout the feature space and instead is dependent on the location of the glass composition in the dimensionally reduced feature space.

Sargin, Irmak↗

An Approach to High-Performance Affordable Housing Using Point-Source Space Conditioning

This project explored the use of minisplit ductless heat pumps in combination with small through-wall transfer fans to provide space conditioning in small single-story homes, including manufactured homes and homes built by Habitat for Humanity. The objectives were to reduce space-conditioning energy consumption by 50% compared to the 2009 International Energy Conservation Code (ICC 2009) while maintaining home affordability and thermal comfort. The strategy to achieve this goal also included a highly efficient thermal envelope to reduce space-conditioning loads.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Plasma in Saturn's Nightside Magnetosphere and the Implications for Global Circulation

We present a bulk ion flow map from the nightside, equatorial region of Saturn's magnetosphere derived from the Cassini CAPS ion mass spectrometer data. The map clearly demonstrates the dominance of corotation flow over radial flow and suggests that the flux tubes sampled are still closed and attached to the planet up to distances of 50RS. The plasma characteristics in the near-midnight region are described and indicate a transition between the region of the magnetosphere containing plasma on closed drift paths and that containing flux tubes which may not complete a full rotation around the planet. Data from the electron spectrometer reveal two plasma states of high and low density. These are attributed either to the sampling of mass-loaded and depleted flux tubes, respectively, or to the latitudinal structure of the plasma sheet. Depleted, returning flux tubes are not, in general, directly observed in the ions, although the electron observations suggest that such a process must take place in order to produce the low-density population. Flux-tube content is conserved below a limit defined by the mass-loading and magnetic field strength and indicates that the flux tubes sampled may survive their passage through the tail. The conditions for mass-release are evaluated using measured densities, angular velocities and magnetic field strength. The results suggest that for the relatively dense ion populations detectable by the ion mass spectrometer (IMS), the condition for flux-tube breakage has not yet been exceeded. However, the low-density regimes observed in the electron data suggest that loaded flux tubes at greater distances do exceed the threshold for mass-loss and subsequently return to the inner magnetosphere significantly depleted of plasma.

Saturn↗

MFVI Energy Efficiency Audit Training Module 2.1: Plug Loads [Slides]

This guide is designed to help trained energy efficiency professionals conduct an energy efficiency audit for commercial and industrial buildings, particularly for micro-, small-, and medium-sized businesses in Mexico. This guide is focused on auditing plug load systems. As such, it will assist its user in documenting the plug loads in the space and then identifying the most efficient means of delivering those plug loads.

21CPP↗

Development of A Maximum Anti-Slosh Baffle Pressure Load Model

The sloshing of propellants can affect the stability of a spacecraft and the integrity of the tank structure. Undesirable sloshing can be controlled by the addition of anti-slosh baffles, and the spacing and configuration of baffles are driven by damping requirements. The structural design of the baffle is determined after consideration of many factors, such as the strength and rigidity needed to support the baffle for its lifetime. Therefore, knowledge of distributed pressure loading is important for detailed structural design. In addition, the resultant force and moment produced by the distributed pressure are of direct importance to the design of a vehicle’s control system. Previous experimental investigations have been conducted to determine the liquid pressure loads and slosh damping associated with a rigid ring baffle. The results suggested that when the nondimensional velocity parameter is larger than 1.0, the theories agree with the test. However, when the velocity parameter is less than 1.0, all theories are nonconservative and under-predict the pressure loads. The present study has derived a maximum pressure load on the slosh baffle based on the energy conservation principle. It is verified from CFD that pressure in the slosh flow field can be decomposed into static and transient components. The CFD results confirm that there is a phase shift in pressure across the baffle, which depends on the fluid damping. Higher damping leads to a higher phase shift. The CFD investigation further verifies the proposed theory: the maximum pressure load occurs when the phase shift is 90 degrees. A comparison of the present computational results to the previous comprehensive experimental data validates the maximum pressure theory. When the baffle is submerged, the maximum pressure theory envelopes all the experimental data points.

CFD↗

Evaluation of bead-stiffened metal panels

Potential weight efficiency for bead-stiffened panels has been demonstrated through fabrication and testing. Theoretically optimum design concepts were identified, and small specimens were tested under combined compression, shear, and bending to determine local buckling failure loads and to verify theory. Large optimized panels were then designed and tested under combined loads. Correlation of test data for large circular tubular panels with theory was conservative and consistent, and indicated reliable and acceptable design theory. Tests of fluted tubular panels indicated general instability failures at loads far below the design values due to nonlinear distortions. Further study of the fluted tubular configuration will be required if its potential weight efficiency is to be attained.

Shideler, J. L.↗

An Open-Source Decarbonization Analytics Framework: Designing for Low-Carbon Emission Districts and Communities: Preprint

This paper introduces an open-source analytics framework designed to assist in creating low or net-zero carbon buildings and urban districts. Integrated within URBANopt, an open-source platform for energy analysis in districts and communities, this framework equips researchers, architects, engineers, and other stakeholders with tools to evaluate the carbon footprint implications of their design choices. The framework enables the analysis of various scenarios, incorporating both historical and future emission factors, and can span across different climate zones, each with distinct grid and emissions characteristics. The results showcase the framework's capability to evaluate the impact of design upgrades and control strategies on carbon emissions in districts and communities. An illustrative analysis using a hypothetical district in Denver, Colorado, shows reduced emissions from energy efficiency upgrades and control strategies, highlighting the sensitivity in their effects on emissions and energy use.

buildings energy efficiency↗

Generating realistic building electrical load profiles through the Generative Adversarial Network (GAN)

Building electrical load profiles can improve understanding of building energy efficiency, demand flexibility, and building-grid interactions. Current approaches to generating load profiles are time-consuming and not capable of reflecting the dynamic and stochastic behaviors of real buildings; some approaches also trigger data privacy concerns. In this study, we proposed a novel approach for generating realistic electrical load profiles of buildings through the Generative Adversarial Network (GAN), a machine learning technique that is capable of revealing an unknown probability distribution purely from data. The proposed approach has three main steps: (1) normalizing the daily 24-hour load profiles, (2) clustering the daily load profiles with the k-means algorithm, and (3) using GAN to generate daily load profiles for each cluster. The approach was tested with an open-source database – the Building Data Genome Project. We validated the proposed method by comparing the mean, standard deviation, and distribution of key parameters of the generated load profiles with those of the real ones. The KL divergence of the generated and real load profiles are within 0.3 for majority of parameters and clusters. Additionally, results showed the load profiles generated by GAN can capture not only the general trend but also the random variations of the actual electrical loads in buildings. We report the proposed GAN approach can be used to generate building electrical load profiles, verify other load profile generation models, detect changes to load profiles, and more importantly, anonymize smart meter data for sharing, to support research and applications of grid-interactive efficient buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗