PIE Approaches to LOCA Specimens
Initial planning for performing quantitative analysis on LOCA tested specimens
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
SEARCH · Engineering Papers
Results for “Performance Analysis”
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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Performance Demonstration and Analytical Support to Accelerate Hydrogen Technology Commercialization in the U.S.
This presentation summarizes some of NREL's capabilities to support the U.S. hydrogen strategy to increase the U.S. hydrogen market from 10 MMT/yr to 50 MMT/yr, supply it with clean hydrogen production for use in multiple sectors. It highlights several capabilities that NREL has to perform demonstrations, analysis, and safety and sensor technologies.
analysis↗
MORPHOLOGICAL AND RADIATION DAMAGE INFORMED THERMAL PROPERTY PREDICTION IN SCALED GEOMETRIC DOMAINS
This proposed work has the potential to rewrite the way the nuclear industry investigates new fuel and nuclear material designs. The current rubric of nuclear material design has myriad steps in the process, and while certain physics are modeled accurately, each step must be connected in order to obtain an entire description of the process. At present, neutronic, thermal, microstructural, fission product chemistry and migration, and radiation defect analysis (hereafter referred to together as “combined analysis”) are performed, albeit separately. There is no existing method which combines these physics in an attempt to understand the natural interactions between these phenomena. Consequently, the timeline for design, fabrication, experiment, validation, and licensing can take years. A disruptive approach is required to accelerate the development of new technology. This proposed undertaking creates a validated computational framework, generating a new microscopic-to-macroscopic methodology yielding thermal property predictions for nuclear fuels and materials at an engineering spatial scale.
11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
Porous membrane enabled mass spectrometry characterization of microfluidic devices
A system for sampling a liquid includes a sample fluid conduit including a membrane having pores. The membrane prevents the passage of the sample liquid through the pores at a first pressure of the sample liquid in the sample fluid conduit. A surface sampling capture probe has a distal end. The capture probe includes a solvent supply conduit and a solvent exhaust conduit. A solvent composition flowing at the distal end of the capture probe establishes a liquid junction with the membrane and establishes a second pressure within the liquid junction at the membrane. The second pressure is lower than the first pressure. Sample liquid will be drawn through the pores of the membrane by the second pressure at the liquid junction. A method for sampling a liquid and for performing chemical analysis on a liquid are also disclosed.
Cahill, John F.↗
User Acceptance of Shared Autonomous Vehicles
A dissertation is proposed to explore user acceptance of shared autonomous vehicles (SAVs). SAVs are facing limited user acceptance. To systematically tackle the user acceptance barriers of SAVs, the main problem can be disintegrated into two sub-problems of user acceptance of autonomous vehicles (AVs) and ridesharing. The comfort of the ride experience in AVs is a determinant of user acceptance. Understanding the influential factors and developing methodologies to quantify human comfort in AVs are essential to facilitating future research to improve human comfort in AVs. The current pooled rideshare (PR) service closely resembles the anticipated future of SAVs. Understanding why users prefer or refuse to use PR at the current stage prepares SAVs for broader acceptance in the future. Until now, a series of peer-reviewed publications have been published to achieve the technical goals. Two simulator-based user studies were conducted to instrument the research on human comfort in AVs. Statistical analysis was performed to identify the crucial vehicular behavioral factors of human comfort in AVs. The influential factors of human comfort in AVs and methodologies to quantify and detect human comfort in AVs were investigated. Two survey-based studies were deployed to facilitate the investigation of user acceptance of rideshare services. The influential factors of users' willingness to consider PR were explored and identified, and the choice behaviors in ridesharing services were comprehensively modeled and analyzed. The proposed research answers a series of fundamental questions regarding the user acceptance of SAVs. For the branch of user acceptance of AVs, the research generated guidelines for improving passenger comfort in AVs by identifying a series of autonomous driving factors of passenger comfort. The research also provides fundamental tools to estimate human comfort levels for future research and in-AV applications. For the branch of user acceptance of PR, the research provided user acceptance-aware vehicle, service, and policy design insights that can promote the usage of PR.
Su, Haotian↗
Serpent - Bison - THM Preliminary Multiphysics Modeling of a Nuclear Thermal Propulsion System Fuel Assembly
This work demonstrates the Monte Carlo neutronic and Thermo-Hydraulic coupling scheme using the Serpent code and MOOSE application Bison and Thermo Hydraulic Module. The coupling scheme is then applied to the reference BWX Technologies Nuclear Ther- mal Propulsion system at he fuel assembly level where it’s used to perform an analysis of the isothermal material coefficients and potential material reactivity worth. A method is developed to isolate which feedback effects should be considered for proceeding with reduced order deterministic neutronic modeling where branch off analysis must be con- ducted. The convergence behavior of the coupling scheme is demonstrated where it fol- lows the standard Picard iteration approach. Verification studies for the method of deduc- ing relevant feedback effects is also demonstrated.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
How does drought affect residential water demand and price elasticity?
Urban water scarcity is an important social and economic concern, particularly as the intensity, duration, and frequency of droughts is increasing in many regions. We consider whether drought induces changes to water demand and the price elasticity of demand for water that may last beyond a drought’s official end date. If drought shocks prompt long-term changes in water demand behavior, and these changes occur at broad geographic scale, they could have important implications for modeling adaptive responses to water scarcity. We assemble a novel dataset on residential water demand and pricing in the western United States to test empirically for effects of drought on water demand and price elasticity. We perform our analysis with aggregate quantity, price, and drought data, accounting for endogenous prices under increasing-block water tariffs and using both average and marginal water fees in estimating water demand functions. Results are consistent with the hypothesis that households may become less price-sensitive after exposure to drought. However, we find no systematic evidence of long-run, drought-related reductions in water demand, itself.
demand hardening↗
PSA 2025 Presentation: "Modeling and Sensitivity Analysis of a Generation IV Pebble Bed Reactor Using MELCOR 2.2"
Accompanying the advancement of reactor technologies is the need for computational modeling and simulation to predict their behavior under normal operating conditions and accident scenarios. New Generation IV reactor designs which employ non-conventional fuel have a particular need for modeling the behavior and release of radionuclides and other material from the fuel. In this work, MELCOR version 2.2, a system-level safety and accident scenario code developed by Sandia National Laboratories, was used to model a 200-MWth pebble bed modular reactor and calculate the inventories of circulating and deposited graphite, metal dust, and elemental components released from the fuel elements. A base case modeling the reactor under standard operating conditions was calculated using MELCOR and the inventories were extrapolated to 30 years of operation time using a logarithmic regression fit. A sensitivity analysis was also performed in which several key parameters for the base case model were modified to explore the effect of these changes on the inventories calculated by MELCOR. A set of transient scenario simulations for a depressurized loss of forced cooling (DLOFC) accident were also performed. The results of the sensitivity analysis and transient simulations are reported and discussed in relation to the modeling techniques used for this study.
22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
Precision Kinematic Sunyaev--Zel'dovich Measurements Across Halo Mass and Redshift with DESI DR2 and ACT DR6: Part II. Bright Galaxy Survey and Emission-Line Galaxies
We present the first high-significance spectroscopic stacked kinetic Sunyaev-Zel'dovich (kSZ) measurements of circumgalactic gas profiles for both Bright Galaxy Survey (BGS) and Emission Line Galaxy (ELG) tracers, combining DESI Data Release 2 with ACT Data Release 6. Using reconstructed line-of-sight velocities from the DESI galaxies and high-resolution ACT temperature maps, we detect the kSZ signal at high significance, reaching signal-to-noise ratios of up to $\sim$9 for BGS and $\sim$7.5 for ELGs in optimal stellar-mass selections. Together with the LRG measurements presented in Paper I, these constitute the most significant kSZ detections from any spectroscopic survey to date. We perform the analysis in both real and harmonic space, obtaining consistent results. By splitting both tracers into stellar-mass bins, we study the scaling of the kSZ amplitude with galaxy properties. Combining the kSZ measurements with ACT Data Release 6 (DR6) CMB lensing maps enables a joint calibration of the galaxy-halo connection and the gas fractions of host halos. For the BGS galaxies, we observe low gas fractions around the virial radius relative to standard expectations, likely attributable to active galactic nuclei (AGN) activity. We find some evidence for higher-mass halos retaining a larger fraction of their baryons, consistent with more efficient feedback in lower-mass systems. For the ELG sample, dominated by blue, star-forming galaxies, we provide the first detection of the gas distribution in ELG host halos. The ELGs appear to exhibit relatively high gas fractions, which points to the possibility of weaker feedback (due to e.g. low AGN and supernova feedback activity) at their mass scale. Finally, we present generalized Navarro-Frenk-White (GNFW) fits to the harmonic-space measurements, providing a compact parametrization of gas profiles for forward modeling in large-scale structure analyses.
Hadzhiyska, B. [Cambridge U.; Cambridge U., Inst. ↗
HotCell Components
To support operations in the HFEF Hot Cell and the FCF Hot Cell, multiple components were designed to support the Bottle Cutter Project and the Sodium Loop Project. These components were designed and analyzed to ensure they can function in their environment and be operated remotely. FEA analysis were performed, prototypes were made, and parts were manufactured to complete this project. This poster documents these parts and test results.
11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
ECAR-5127 Rev 1 Evaluation of the MARVEL Reactor Inhalation Dose Consequences
The following dose consequence analysis is performed to support the preliminary Microreactor Applications Research Validation and Evaluation Project (MARVEL) design effort. The purpose of the MARVEL project is to develop a nuclear microreactor applications test bed at Idaho National Laboratory (INL) to perform research and development on various operational features of microreactors to ultimately improve integration of microreactors to end-user applications. The MARVEL concept is a 100 kilowatt (kW) thermal (kWth) and approximately 20-kW electric (kWe) generating microreactor. The MARVEL system will be located in the INL TREAT facility in the north high-bay equipment pit. This ECAR considers the bounding release fractions of the MARVEL reactor concept and documents the dose consequences to the public and collocated worker.
21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗
Optimal Hairpin Winding Configuration for EV Traction Motors to Enhance Active CMV Cancellation Capability of NPL.X Inverter
Active common-mode voltage (CMV) cancellation in neutral-point-less (NPL.X) inverter is an effective approach for reducing common-mode electromagnetic interference and alleviating voltage stress associated with high-speed switching in EV traction drives. However, the existing hairpin winding configuration often exhibits impedance imbalance due to slot leakage inductance and manufacturing constraints, limiting the effectiveness of active CMV cancellation. This paper investigates symmetric hairpin winding configurations for a dual-three-phase EV traction machine to improve impedance symmetry. Considering the manufacturing constraints of six-layer hairpin windings, four feasible symmetric winding configurations are analyzed. Two-dimensional finite-element analysis is performed to extract the impedance parameters of each configuration. The extracted impedance parameters are used to quantify the impedance mismatch between complementary phase pairs and evaluate its influence on active CMV cancellation. The results show that the fully interleaved winding configuration achieves perfectly balanced phase impedances with 0 % mismatch, whereas the mismatch in the other configurations ranges from approximately 2.4 % to 0.8 %. Consequently, the resulting total CMV overshoot is significantly suppressed to near zero voltage under high-voltage and high switching frequency operating conditions, demonstrating the importance of winding symmetry for maximizing the active CMV cancellation capability of the NPL.X inverter.
Lee, Kangbeen [Purdue Univ., West Lafayette, IN (U↗
Hybrid Cooling and Water Treatment for Resilient, Water-Self-Sufficient Data Centers
The continued growth of data center infrastructure is intensifying demand for freshwater resources, particularly in water-stressed regions, and is increasingly limiting sustainable capacity expansion. This work investigates a conceptual hybrid system that integrates freeze desalination with ultrasonic-assisted ice separation to enable on-site production of pure water from diverse sources, including seawater, brackish groundwater, and reclaimed industrial or agricultural wastewater. Simultaneously, the system produces low-temperature cooling streams that enhance heat removal in high power density computing environments. A process-level thermodynamic analysis is performed across a range of boundary and operating conditions, including variations in feed concentration, freezing temperature, and mass flow rate. The results are presented as performance curves relating feedwater concentration and target purified water output to the corresponding intake flow requirements, enabling estimation of source water demand per unit of Information Technology Equipment (ITE) energy consumption (kWh) across varying data center scales and operational scenarios. The corresponding electrical energy consumption for integrated cooling and water treatment is also evaluated as a function of system operating parameters and target water production levels. These results provide a basis for evaluating system feasibility across different conditions and for identifying parameter ranges in which integrated water treatment and cooling improve resource efficiency, thermal performance, and operational flexibility in data centers.
Elhefny, Aly [ORNL] (ORCID:0000000284907923)↗
Determining the Efficiency of EMPHATICs Silicon Strip Detectors (SSDs)
EMPHATIC is an experiment at Fermilab which aims to reduce current neutrino flux uncertainties. This report discusses the limitations current neutrino flux uncertainties places on large scale neutrino experiments, provides background on the EMPHATIC experiment, and details the project of determining the efficiency of the Silicon Strip Detectors (SSDs) used in EMPHATIC. As part of the data analysis process and in order to increase the accuracy of EMPHATIC’s simulations a representation of efficiency of each SSD is required. To achieve this a data-driven analysis was performed on EMPHATIC's collected data using the Root and Art frameworks. Visual and numerical representations of efficiency were determined. The average efficiency over all SSDs is 98.58\%, however this number deflated as it includes known bad channels.
Olson, V. [Illinois U., Urbana (main)]↗
Comparative PV LCOE Calculator (Comparative Photovoltaic Levelized Cost of Energy Calculator) [SWR-20-86]
The calculator calculates levelized cost of energy (LCOE) for photovoltaic (PV) systems based on cost, performance, and reliability inputs for a baseline and a proposed technology. The user can choose inputs and watch the effect on LCOE to determine whether a proposed technology is cost-effective, perform trade-off analysis among different technology options, and do break-even analysis of cost or performance.
Silverman, Timothy↗
Preliminary Theoretical Analysis of Mixed Precision Krylov Subspace Methods (Q3 Report)
The third quarter of the project was spent performing theoretical finite precision analysis of Krylov subspace method variants that use mixed precision. Our focus here is on the Conjugate Gradient (CG) method and the Lanczos method. We have performed an analysis of maximum attainable accuracy for the classical CG method in which 3 precisions are used: a working precision ε, a precision ε IP for the inner product computations, and a precision ε MV for the matrix-vector products. Our results show that performing inner product computations in lower precision does not affect the attainable accuracy. Further, we have performed a complete error analysis of the s-step Lanczos algorithm. In this case, we show that the numerical behavior of the algorithm can be significantly improved by using extra precision in a small part of the computation. We summarize the main theorems in the remainder of the document. Other activities include attending biweekly xSDK meetings. The subsequent quarter will be spent finalizing these results into technical reports and/or manuscripts for submission to journals, as well as identifying opportunities for future work.
97 MATHEMATICS AND COMPUTING↗
Uncertainty analysis of Resource Demand Model for Covid-19
As part of the Department of Energy response to the novel coronavirus pandemic of 2020, a modeling effort was sponsored by the DOE Office of Science. One task of this modeling effort at Sandia was to develop a model to predict medical resource needs given various patient arrival scenarios. Resources needed include personnel resources (nurses, ICU nurses, physicians, respiratory therapists), fixed resources (regular or ICU beds and ventilators), and consumable resources (masks, gowns, gloves, face shields, sedatives). This report documents the uncertainty analysis that was performed on the resource model. The uncertainty analysis involved sampling 26 input parameters to the model. The sampling was performed conditional on the patient arrival streams that also were inputs to the model. These patient arrival streams were derived from various epidemiology models and had a significant effect on the projected resource needs. In this report, we document the sampling approach, the parameter ranges used, and the computational workflow necessary to perform large-scale uncertainty studies for every county and state in the United States.
59 BASIC BIOLOGICAL SCIENCES↗
Inverse Analysis with Variational Autoencoders: A Comparison of Shallow and Deep Networks
Inverse problems are applied to determine unknown properties by matching observational data with a physical model that often takes many parameters as input. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented involving regularization with a technique known as a variational autoencoder (VAE), which is trained to map a high-dimensional parameter space with a complex structure to a low-dimensional latent space with a simple structure. We apply this approach to unconditioned realizations of the parameters (heterogeneous hydraulic fields) for a hydrogeological inverse problem. Two types of hydraulic conductivity fields are used to evaluate the characterization for the different levels of heterogeneity complexity of the physical inputs. This approach keeps the computational cost of generating the training data low. The reason is unconditioned realizations neither rely on the observational data used to perform the inverse analysis nor require any groundwater flow model forward runs. In addition, this approach applies regularization on a low-dimensional latent space from the VAE and increases optimization efficiency through automatic differentiation. Furthermore, two different neural network (NN) structures are tested for their utility in using the VAE for inverse analysis. The performance of a deep, convolutional neural network strongly depends on the dimensionality of the latent space, which requires tuning. In contrast, a shallow, dense neural network provides consistently accurate characterization without tuning. Furthermore, our approach evaluates the advantages of the shallow, dense neural network over the deep, convolutional one and enables future application to a wide range of inverse problems.
97 MATHEMATICS AND COMPUTING↗