Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Conditional Distribution”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Multisource Data Fusion Outage Location in Distribution Systems via Probabilistic Graphical Models

Efficient outage location is critical to enhancing the resilience of power distribution systems. However, accurate outage location requires combining massive evidence received from diverse data sources, including smart meter (SM) last gasp signals, customer trouble calls, social media messages, weather data, vegetation information, and physical parameters of the network. This is a computationally complex task due to the high dimensionality of data in distribution grids. In this paper, we propose a multi-source data fusion approach to locate outage events in partially observable distribution systems using Bayesian networks (BNs). A novel aspect of the proposed approach is that it takes multi-source evidence and the complex structure of distribution systems into account using a probabilistic graphical method. Our method can radically reduce the computational complexity of outage location inference in high-dimensional spaces. The graphical structure of the proposed BN is established based on the network’s topology and the causal relationship between random variables, such as the states of branches/customers and evidence. Utilizing this graphical model, accurate outage locations are obtained by leveraging a Gibbs sampling (GS) method, to infer the probabilities of de-energization for all branches. Compared with commonly-used exact inference methods that have exponential complexity in the size of the BN, GS quantifies the target conditional probability distributions in a timely manner. As a result, a case study of several real-world distribution systems is presented to validate the proposed method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1987

Intercomparison among plasma wake models for plasmaspheric and ionospheric conditions

The angular distributions of ions in the wake of a body moving through a space plasma computed from three different models are compared in order to investigate wake current depletion ratios under conditions simulating the topside ionosphere and plasmasphere. Results demonstrate the importance of taking into account the thermal flux at low Mach numbers and the angular acceptance of ion detectors in making theory-experiment comparisons. For all models considered, gradients in the angular variations of the fluxes are shown to be steeper near the wake-ambient interface than closer to the maximum rarefaction region.

Samir, U.↗
DOE OSTI2024

DECOVALEX-2023: Task D Final Report

Task D of DECOVALEX-2023 is focused on the simulation of the coupled thermal hydraulic-mechanical (THM) behaviour in the full-scale engineered barrier system (EBS). The Horonobe EBS experiment is the demonstration of the full-scale EBS in the underground research laboratory (URL) (performed by JAEA in the Horonobe URL in Japan). Task D consisted of the three steps, a preliminary step (Step 0), simulation of the laboratory tests (Step 1) and simulation of the in-situ full-scale EBS experiment (Step 2). Since the Horonobe EBS experiment demonstrates the vertical emplacement option of the EBS, the experiment gallery is also backfilled with the backfill material. Therefore, interaction between the EBS and the backfill material can also be demonstrated, such as deformation (change of density) of the buffer material. The underground water in the Horonobe URL is saline. This fact adds chemical processes to THM behaviour. For example, mechanical properties (such as swelling pressure of the buffer material and backfill material) and hydraulic properties (such as permeability of the buffer material and backfill material) change depending on the water chemistry. Task D was therefore a challenging Task focused on not only the relatively simple THM behaviour but also complex THM behaviour including chemical processes. Six research teams (BGR, CAS, JAEA, KAERI, SNL and Taipower) participated the Task D. BGR, CAS, JAEA, KAERI and Taipower research teams selected a THM approach, while the SNL research team selected a TH approach. Step 1 involved the simulation of laboratory test results and was important to check the numerical codes developed by the research teams. Step 1 was divided into four sub steps. The simulation results through the Step 1 identified the parameters for simulation of the Step 2. Basic parameters of the materials (buffer material, backfill material, rock mass, concrete, sand) were provided by JAEA. Special parameters which research team needed were identified by back analysis of Step 1. Most notably the mechanical behaviour of swelling and displacement depended on the applied model (elastic model or elastoplastic model). Parameters such as Young’s modulus were found to need smaller values than characterised in the fundamental laboratory test results (Step 1-1, 1-2) for the elastic model. Although laboratory experiments are usually simple, test results contained some error. For example, if the saturation level is 100 % or higher, it should be considered an error. This situation was presented in the Step 1-3. A possible reason is that the buffer material is a mixture of bentonite and silica sand. When a specimen is cut to measure volume or weight, sand grains will affect the measurement data. In Step 2, boundary conditions such as temperature on the surface of the simulated overpack, heater power of the electrical heaters installed in the simulated overpack, injection pressure and inflow rate of the test water, were applied. The outer boundary conditions can be selected using measured data (injection pressure and inflow rate of the test water that is controlled by the injection systems installed in the sand layer around the buffer material and in the boundary between backfill material and concrete support). Since such measured data has some noise, research teams developed their own simplified boundary conditions. Inner boundary conditions can be selected using measured data as heater power and temperature on the surface of the simulated overpack. These data also contain some noise, so research teams developed their own simplified developed boundary conditions. Task D validated various approaches thorough the simulation of the in-situ full scale EBS system including backfill of the gallery: variations in the coupling processes (THM or THC), analysis codes, and boundary conditions. Temperature distribution in the buffer material was simulated well by all research teams. This means thermal behaviour is not sensitive to the simulation approaches. Although the water content distribution on the outside of the buffer material was well simulated by all research teams, the simulation results differ from the measured values inside the buffer material (at the centre and inside, near the simulated overpack). The buffer material is made from tap water, but in the in-situ experiment, saline groundwater infiltrates the buffer material. Therefore, the selection of the hydraulic parameters of the buffer material greatly affects the simulation results of the re saturation behaviour of the buffer material. In the Horonobe EBS experiment, measured values suitable for validating the simulation results were not obtained near the simulated overpack. When simulating the pressure and deformation of the buffer material, the measurement data is easily affected by the installation conditions of the measurement sensors, so verifying the measurement data itself remains an issue. Mechanical simulation results differ depending on whether they are considered as elastic or elastoplastic phenomena. The accuracy of measured in-situ data can be assessed by detailed analysis comparing sampling specimen analysis and measured data. The Horonobe EBS experiment is scheduled to be dismantled in the future (FY2026 and 2027). This detailed dismantling investigation will finally confirm the measured data.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Examining the Impacts of Great Lakes Temperature Perturbations on Simulated Precipitation in the Northeastern United States

Most inland water bodies are not resolved by general circulation models, requiring that lake surface temperatures be estimated. Given the large spatial and temporal variability of the surface temperatures of the North American Great Lakes, such estimations can introduce errors when used as lower boundary conditions for dynamical downscaling. Lake surface temperatures (LSTs) influence moisture and heat fluxes, thus impacting precipitation within the immediate region and potentially in regions downwind of the lakes. For this study, the Advanced Research version of the Weather Research and Forecasting Model (WRF-ARW) was used to simulate precipitation over the six New England states during a 5-yr historical period. The model simulation was repeated with perturbed LSTs, ranging from 10°C below to 10°C above baseline values obtained from reanalysis data, to determine whether the inclusion of erroneous LST values has an impact on simulated precipitation and synoptic-scale features. Results show that simulated precipitation in New England is statistically correlated with LST perturbations, but this region falls on a wet–dry line of a larger bimodal distribution. Wetter conditions occur to the north and drier conditions occur to the south with increasing LSTs, particularly during the warm season. Additionally, the precipitation differences coincide with large-scale anomalous temperature, pressure, and moisture patterns. Care must therefore be taken to ensure reasonably accurate Great Lakes surface temperatures when simulating precipitation, especially in southeastern Canada, Maine, and the mid-Atlantic region.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Shape Measurement of Large Aerospace Structures Using Sensitivity Electrical TDR Distributed Strain Sensor

Electrical time domain reflectometry (ETDR) sensing technique can be best described as "closed-loop radar," where the information is derived from the reflections of a voltage pulse sent through a transmission medium. The ETDR sensing technique is a well-developed method and has been widely used to locate and evaluate discontinuities in long coaxial power transmission cables. The ETDR technique provides a true distributed sensing capability which can not only sense the distributed loading condition of the structure but also can pin-point the location of disturbance, such as the locations of stress concentration and structural damages. Proof-of-concept experiments have been conducted using photoelastic specimens with embedded commercial coaxial cables, i.e., RG85/U and RG174, to demonstrate the stress/strain sensing capability of ETDR sensors for structural health monitoring application. Although the test results showed that the ETDR sensor signals capture specimen deformation pattern both in bending and tension and indicate the location and type of crack damages of the photoelastic specimen; yet, the low signal-to-noise ratio of the sensor signal smears the details of the strain measurement that the ETDR signals can convey. A high-sensitivity ETDR coaxial strain sensor prototype newly developed at Clark Atlanta University will be presented. The construction of the prototype sensing cable as well as its electrical properties relevant to distributed strain sensing application will be shown in details. Test results of the sensitivity and tension responses of the ETDR signal of the prototype sensor will be presented and compared with those of commercial coaxial cables. Promising potentials of the ETDR distributed strain sensing method for shape measurement application of large aerospace structures will also be demonstrated using long slender beam with surface-bonded ETDR distributed strain sensor.

Lin, Mark W.↗
NASA NTRS1977

Temperature distribution in the human body under various conditions of induced hyperthermia

A mathematical model based on heat balance equations was developed for studying temperature distribution in the human body under deep hyperthermia which is often induced in the treatment of malignant tumors. The model yields results which are in satisfactory agreement with experimental data. The distribution of temperature under various conditions of induced hyperthermia, i.e. as a function of water temperature and supply rate, is examined on the basis of temperature distribution curves in various body zones.

Korobko, O. V.↗
DOE OSTI2022

134 billion intersecting brane models

The landscape of string vacua is very large, but generally expected to be finite in size. Enumerating the number and properties of the vacua is an important task for both the landscape and the swampland, in part to gain a deeper understanding of what is possible and “generic”. We obtain an exact counting of distinct intersecting brane vacua of type IIA string theory on the T 6 /Z 2 × Z 2 orientifold. Care is taken to only count gauge-inequivalent brane configurations. Leveraging the recursive nature by which branes may be added together one-by-one, we use dynamic programming to efficiently count the number of solutions of the tadpole, K-theory and supersymmetry consistency conditions. The distributions of 4D gauge group rank and complex structure moduli for the entire ensemble of intersecting brane vacua are presented. The methods we developed here may be useful in obtaining sharp upper and lower bounds on other corners of the landscape.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Characterization of the microstructure of yttrium hydride under proton irradiation

High moderation per unit volume solid moderator materials like yttrium hydride (YH x ) are necessary for compact nuclear microreactors. However, the phase stability and hydrogen transport processes of YH x under high-temperature irradiation are largely unknown. Proton irradiation was conducted on YH x at 300 °C and 580 °C to 0.2 dpa using 1 MeV or 2 MeV protons in a high-vacuum environment. The hydrogen concentration was determined before and after irradiation using elastic recoil detection analysis, and microstructural evolution was examined via post-irradiation scanning transmission electron microscopy and Raman spectroscopy. Dislocation loops and cavities were observed in all conditions; their distribution was correlated with the bombarding proton energy and ion irradiation temperature. This work revealed that hydrogen retention is proportional to the formation of traps for hydrogen gas atoms and identified pathways for hydrogen release. The relative contributions of bulk or fast diffusion paths, such as grain boundaries, delamination boundaries, and stacking faults are discussed; the primary mechanisms of hydrogen loss are likely based on diffusion, ruling out artefacts of the experimental design. In conclusion, the study suggests proton irradiation may be a strong surrogate to study hydrogen transport in hydride moderator materials under irradiation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Development and Validation of the Near-Miss Safety Score (NMSS) Framework for Heavy-Duty Vehicle Safety Assessment

Heavy-duty commercial vehicles present unique safety challenges due to their size, articulation dynamics, and operational complexity. As Advanced Driver Assistance Systems (ADAS) and Automated Driving Systems (ADS) become more common in Class 8 tractor-trailers, traditional crash-based metrics are no longer sufficient to evaluate safety performance. This study introduces the Near-Miss Safety Score (NMSS)—a quantitative, physics-informed framework developed as a leading indicator of safety for advanced commercial vehicle technologies. NMSS quantifies how close a vehicle or operator comes to a collision or safety-critical event by integrating vehicle kinematics (relative distance, velocity, and acceleration) with driver or system response latency and time-to-collision. A modifier function adjusts the base score for vehicle-specific and environmental factors such as trailer articulation, load distribution, braking condition, and roadway environment. The framework enables systematic evaluation of ADAS/ADS performance under a range of operational and degraded conditions. By capturing near-miss dynamics rather than relying on crash data, NMSS provides a proactive approach to risk assessment, accelerates technology validation, and enhances interpretability for regulators and fleet operators. The proposed NMSS was validated using data collected from a motorcoach platform, demonstrating the framework’s applicability to heavy-duty safety evaluation and performance benchmarking. Results and key insights are presented in this paper.

Siekmann, Adam [ORNL] (ORCID:0000000284653935)↗
DOE OSTI2026

Multi-Modal Bayesian Neural Network Surrogates with Conjugate Last-Layer Estimation

As data collection and simulation capabilities advance, multi-modal learning, the task of learning from multiple modalities and sources of data, is becoming an increasingly important area of research. Surrogate models that learn from data of multiple auxiliary modalities to support the modeling of a highly expensive quantity of interest have the potential to aid outer loop applications such as optimization, inverse problems, or sensitivity analyses when multi-modal data are available. We develop two multi-modal Bayesian neural network surrogate models and leverage conditionally conjugate distributions in the last layer to estimate model parameters using stochastic variational inference (SVI). We provide a method to perform this conjugate SVI estimation in the presence of partially missing observations. Here, we demonstrate improved prediction accuracy and uncertainty quantification compared to unimodal surrogate models for both scalar and time series data.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Maximally entangled gluons for any x

Individual quarks and gluons at small x inside an unpolarized hadron can be regarded as Bell states in which qubits in the spin and orbital angular momentum spaces are maximally entangled. Using the machinery of quantum information science, we generalize this observation to all values 0 < x <1 and describe gluons (but not quarks) as maximally entangled states between a qubit and a qudit. We introduce the conditional probability distribution P⁡(l z |s z ) of a gluon’s orbital angular momentum l z given its helicity s z . Restricting to the three states l z =0,±1, which constitute a qutrit, we explicitly compute P as a function of x.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Improved Control Strategy of Grid Interface for EV High-Power Dynamic Wireless Charging

This paper proposes a control strategy for the grid interface converter in high-power dynamic wireless charging system (DWCS) to address two issues on distribution network integration. Due to the unique pulsating load profile of DWCS, load transient response capability is critical for the grid interface to maintain the dc-bus voltage stable. Besides, the inherent unbalanced situation of distribution network would lead to 2nd-order oscillations on the dc-bus voltage, which would further affect the stable operation of the entire system. In this paper, the DWCS model is developed, and the relationship between the dc-bus voltage and the input/output power is analyzed. Based on the developed model, a control strategy based on direct power control is presented. Both simulation results and hardware-in-the-loop (HIL) results demonstrate that the proposed control strategy not only improves load transient response capability, but also eliminates the 2nd-order oscillations on the dc-bus voltage under imbalanced distribution network conditions.

Zeng, Rong↗
DOE OSTI2024

Swarm Intelligence Based Optimal Design of Local Volt/Var Control Function for Distributed Energy Resources

The increasing penetration of renewable based distributed energy resources (DERs) in distribution network (DN) leads to larger and more frequent voltage variation in distributions network (DN), thus posing challenges on voltage control. Real-time local voltage control method is a promising solution for the above issue. However, the local voltage control function needs to be customized and optimized according to real distribution system condition. In this paper, a swarm intelligence based Volt/Var control optimal design method (SO-VVC) is proposed to optimize the control function. Compared with existing approaches, the proposed method can not only represent the nonlinear behaviour of power flow but is also computation efficient. The performance of the proposed SO-VVC is demonstrated by case studies on a modified IEEE-123 bus system.

Zhang, Zhengfa [University of Tennessee, Knoxville↗
DOE OSTI2025

Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty

Engineering and applied science rely on computational experiments to rigorously study physical systems. The mathematical models used to probe these systems are highly complex, and sampling-intensive studies often require prohibitively many simulations for acceptable accuracy. Surrogate models provide a means of circumventing the high computational expense of sampling such complex models. In particular, polynomial chaos expansions (PCEs) have been successfully used for uncertainty quantification studies of deterministic models where the dominant source of uncertainty is parametric. We discuss an extension to conventional PCE surrogate modeling to enable surrogate construction for stochastic computational models that have intrinsic noise in addition to parametric uncertainty. We develop a PCE surrogate on a joint space of intrinsic and parametric uncertainty, enabled by Rosenblatt transformations, which are evaluated via kernel density estimation of the associated conditional cumulative distributions. Furthermore, we extend the construction to random field data via the Karhunen–Loève expansion. We then take advantage of closed-form solutions for computing PCE Sobol indices to perform a global sensitivity analysis of the model which quantifies the intrinsic noise contribution to the overall model output variance. Additionally, the resulting joint PCE is generative in the sense that it allows generating random realizations at any input parameter setting that are statistically approximately equivalent to realizations from the underlying stochastic model. The method is demonstrated on a chemical catalysis example model and a synthetic example controlled by a parameter that enables a switch from unimodal to bimodal response distributions.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Thermal Runaway of Li-Ion Cells: How Internal Dynamics, Mass Ejection, and Heat Vary with Cell Geometry and Abuse Type

Thermal runaway of lithium-ion batteries can involve various types of failure mechanisms each with their own unique characteristics. Using fractional thermal runaway calorimetry and high-speed radiography, the response of three different geometries of cylindrical cell (18650, 21700, and D-cell) to different abuse mechanisms (thermal, internal short circuiting, and nail penetration) are quantified and statistically examined. Correlations between the geometry of cells and their thermal behavior are identified, such as increasing heat output per amp-hour (kJ Ah −1 ) of cells with increasing cell diameter during nail penetration. High-speed radiography reveals that the rate of thermal runaway propagation within cells is generally highest for nail penetration where there is a relative increase in rate of propagation with increasing diameter, compared to thermal or internal short-circuiting abuse. For a given cell model tested under the same conditions, a distribution of heat output is observed with a trend of increasing heat output with increased mass ejection. Finally, internal temperature measurements using thermocouples embedded in the penetrating nail are shown to be unreliable thus demonstrating the need for care when using thermocouples where the temperature is rapidly changing. All data used in this manuscript are open access through the NREL and NASA Battery Failure Databank.

25 ENERGY STORAGE↗
DOE OSTI2023

ResStock™ v3.2.0 [SWR-19-15 and SWR-20-07]

The ResStock™ analysis tool was built on NREL's OpenStudio® platform, and is a project geared at modeling existing residential building stocks at national, regional, or local scales with a high-degree of granularity (e.g., one physics-based simulation model for every 200 dwelling units), using the EnergyPlus® simulation engine. Information about ComStock™, a sister tool for modeling the commercial building stock, can be found here: https://www.nrel.gov/buildings/comstock.html This repository contains: Housing characteristics of the U.S. residential building stock, in the form of conditional probability distributions stored as tab-separated value (.tsv) files. Comments at the bottom of each file document data sources and assumptions for each. A library of housing characteristic "options" that translate high-level characteristic parameters into arguments for OpenStudio measures, and which are referenced by the housing characteristic .tsv files and building energy upgrades defined in project definition files Project definition files: v2.3.0 and later: buildstockbatch YML files openable in any text editor v2.2.5 and prior: Project folder openable in PAT Unit-level OpenStudio Measures for automatically constructing OpenStudio Models of each representative dwelling unit model: v3.0.0 and later: OpenStudio-HPXML Measures v2.5.0 and prior: OpenStudio Measures Higher-level OpenStudio Measures for controlling simulation inputs and outputs This repository does not contain software for running ResStock simulations, which can be found as follows: Versions 2.3.0 and later only support the use of buildstockbatch for deploying simulations on high-performance or cloud computing. Version 2.3.0 also removed separate projects for single-family detached and multifamily buildings, in lieu of a combined project_national representing the U.S. residential building stock. See the changelog for more details. Versions 2.2.5 and prior support the use of the publicly available OpenStudio-PAT software as an interface for deploying simulations on cloud computing. Read the documentation for v2.2.5.

Horowitz, Scott↗
DOE OSTI2025

Thermomechanical Modeling and Analysis of a High-Temperature Light Trapping Planar Cavity Receiver

Solar energy harnessed through concentrating solar power (CSP) systems offers a promising path to sustainable energy production, with the efficiency and longevity of these systems relying on key components like solar receivers. This study analyzes the thermomechanical behavior of an innovative enclosed light-trapping solar receiver optimized for particle heating applications. The receiver utilizes sheet metal alloys to form enclosed cavities that reflect and trap incoming solar flux, as well as enclosed channels that contain fluidized particle beds absorbing solar heat. Finite element analysis (FEA) is applied to predict the receiver's thermomechanical performance under extreme solar flux conditions. Temperature distributions from a thermal model simulating a multi-panel assembly at steady state are input into the FEA thermomechanical model for stress analysis. A key aspect of the analysis focuses on evaluating creep-fatigue damage, with a design target of achieving a 30- year service life. Various stress relief techniques are also proposed to extend the receiver's service life. The results highlight the significant impact of the particle-to-wall heat transfer coefficients (HTCs), ranging from 800 W/m2*K to 1400 W/m2*K. The 800 W/m2*K case shows a maximum von Mises stress of 164 MPa, while the 1400 W/m2*K case reduces it to 150 MPa. The creep life increases from 4,000 hrs in the 800 W/m2*K case to over 100,000 hrs in the 1400 W/m2*K case with Inconel 740H used, indicating that higher HTCs reduce stress and extend lifespan. This research advances the design of high-efficiency, low-stress solar receivers for particle-based thermal energy storage in CSP and industrial heating applications.

concentrating solar power↗