Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “VECTORS”

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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Performance of an Astrophysical Radiation Hydrodynamics Code under Scalable Vector Extension Optimization

We present results of a performance study of an astrophysical radiation hydrodynamics code, V2D, on the Arm-based A64FX processor developed by Fujitsu. The code solves sparse linear systems, a task for which the A64FX architecture should be well suited. Here, we performed the performance analysis study on Ookami, an Apollo 80 platform utilizing the A64FX processor. We explored several compilers and performance anal-ysis packages and found the code did not perform as expected under scalable vector extension optimization, suggesting that a “deeper dive” into analyzing the code is worthwhile. However, a simple driver program that exercised basic sparse linear algebra routines used by V2D did show significant speedup with the use of the scalable vector extension optimization. We present the initial results from the study which used V2D on a relatively simple test problem that emphasized the repeated solution of sparse linear systems.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Sparse Binary Matrix-Vector Multiplication on Neuromorphic Computers

Neuromorphic computers offer the opportunity for low-power, efficient computation. Though they have been primarily applied to neural network tasks, there is also the opportunity to leverage the inherent characteristics of neuromorphic computers (low power, massive parallelism, collocated processing and memory) to perform non-neural network tasks. Here, we demonstrate how an approach for performing sparse binary matrix-vector multiplication on neuromorphic computers. We describe the approach, which relies on the connection between binary matrix-vector multiplication and breadth first search, and we introduce the algorithm for performing this calculation in a neuromorphic way. We validate the approach in simulation. Finally, we provide a discussion of the runtime of this algorithm and discuss where neuromorphic computers in the future may have a computational advantage when performing this computation.

Schuman, Catherine↗
DOE OSTI2016

Comparative Visualization of Vector Field Ensembles Based on Longest Common Subsequence

We propose a longest common subsequence (LCS) based approach to compute the distance among vector field ensembles. By measuring how many common blocks the ensemble pathlines passing through, the LCS distance defines the similarity among vector field ensembles by counting the number of sharing domain data blocks. Compared to the traditional methods (e.g. point-wise Euclidean distance or dynamic time warping distance), the proposed approach is robust to outlier, data missing, and sampling rate of pathline timestep. Taking the advantages of smaller and reusable intermediate output, visualization based on the proposed LCS approach revealing temporal trends in the data at low storage cost, and avoiding tracing pathlines repeatedly. Finally, we evaluate our method on both synthetic data and simulation data, which demonstrate the robustness of the proposed approach.

Liu, Richen↗
DOE OSTI2019

Finite-Difference Simulation of Eddy Currents in Nonmagnetic Sheets via Electric Vector Potential

The magnetic excitation of eddy currents in thin metal sheets is a mathematically challenging problem with many practical applications. Since the eddy current density is a solenoidal field on a 2-D plane, we may express it as the curl of a separate vector field with only one scalar component. This new field is governed by a unique form of the vector-Poisson equation that is readily solved numerically through standard finite-difference techniques. For the special case of a weakly induced eddy current, the self-inductance terms can be neglected to produce a sparse system matrix that is easily inverted. For a strongly induced eddy current, self-inductance must be included at the cost of a more complex and dense system matrix. The method is validated against the CST EM Studio software suite by producing nearly identical results in only a tiny fraction of the computational time.

42 ENGINEERING↗
DOE OSTI2017

Dynamic Price Vector Formation Model-Based Automatic Demand Response Strategy for PV-Assisted EV Charging Stations

A real-time price (RTP)-based automatic demand response (ADR) strategy for PV-assisted electric vehicle (EV) Charging Station (PVCS) without vehicle to grid is proposed. The charging process is modeled as a dynamic linear program instead of the normal day-ahead and real-time regulation strategy, to capture the advantages of both global and real-time optimization. Different from conventional price forecasting algorithms, a dynamic price vector formation model is proposed based on a clustering algorithm to form an RTP vector for a particular day. A dynamic feasible energy demand region (DFEDR) model considering grid voltage profiles is designed to calculate the lower and upper bounds. A deduction method is proposed to deal with the unknown information of future intervals, such as the actual stochastic arrival and departure times of EVs, which make the DFEDR model suitable for global optimization. Finally, both the comparative cases articulate the advantages of the developed methods and the validity in reducing electricity costs, mitigating peak charging demand, and improving PV self-consumption of the proposed strategy are verified through simulation scenarios.

14 SOLAR ENERGY↗
DOE OSTI2018

Rapid determination of soil classes in soil profiles using vis–NIR spectroscopy and multiple objectives mixed support vector classification

Summary Visible‐near infrared (vis–NIR) spectroscopy can reveal various soil properties and facilitate soil classification. However, few studies have attempted to classify vertical soil profiles that contain several genetic horizons. Here, we propose the ‘multiple objectives mixed support vector classification’ (MOM–SVC) method to classify soil profiles. A total of 130 soil profiles were collected from genetic horizons in Zhejiang Province, China. After laboratory analysis, soil profiles were classified according to the Chinese Soil Taxonomy system. Vis–NIR spectra were recorded from each genetic horizon of each soil profile and were then pre‐processed. We performed the MOM–SVC method as follows: (i) created a support vector machine (SVM) model (one‐versus‐one approach) using spectral data from all soil horizons in calibration profiles, (ii) applied the SVM model on each horizon of the profile to be predicted, (iii) extracted ‘votes’ from each horizon and mixed (or summarized) them into the votes of each profile to be predicted and (iv) classified each profile by the majority‐voting method. We also investigated whether the additional input of auxiliary soil information (e.g. moist soil colour, soil organic matter and soil texture), which could be measured easily or be well predicted by vis–NIR spectroscopy, could improve the accuracy of soil classification when combined with it. Independent validation results showed that the MOM–SVC method performed better at the soil order level than at the suborder level. Adding auxiliary soil information to the classification model improved the overall accuracy of classification at the soil order level. The proposed MOM–SVC method provides a fast objective diagnostic of soil classes for use in soil surveys and can help to update soil databases when a more objective soil classification system is developed. Highlights The MOM–SVC method can be used to classify soil profiles objectively with a variety of soil horizons. Stratified random sampling was used to quantify prediction uncertainty in classification MOM–SVC can predict soil orders with greater accuracy than suborders. Adding auxiliary soil information into the classification model improved prediction accuracy.

Chen, S.↗
DOE OSTI2014

Search for invisible decays of Higgs bosons in the vector boson fusion and associated ZH production modes

A search for invisible decays of Higgs bosons is performed using the vector boson fusion and associated ZH production modes. In the ZH mode, the Z boson is required to decay to a pair of charged leptons or a b b-bar quark pair. The searches use the 8 TeV pp collision dataset collected by the CMS detector at the LHC, corresponding to an integrated luminosity of up to 19.7 inverse femtobarns. Certain channels include data from 7 TeV collisions corresponding to an integrated luminosity of 4.9 inverse femtobarns. The searches are sensitive to non-standard-model invisible decays of the recently observed Higgs boson, as well as additional Higgs bosons with similar production modes and large invisible branching fractions. In all channels, the observed data are consistent with the expected standard model backgrounds. Limits are set on the production cross section times invisible branching fraction, as a function of the Higgs boson mass, for the vector boson fusion and ZH production modes. By combining all channels, and assuming standard model Higgs boson cross sections and acceptances, the observed (expected) upper limit on the invisible branching fraction at m[H] = 125 GeV is found to be 0.58 (0.44) at 95% confidence level. We interpret this limit in terms of a Higgs-portal model of dark matter interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Search for a heavy resonance decaying to a top quark and a vector-like top quark in the lepton + jets final state in pp collisions at $\sqrt{s} = 13\,\text {TeV} $

Here a search is presented for a heavy spin-1 resonance $\mathrm {Z}'$ decaying to a top quark and a vector-like top quark partner $\text {T} $ in the lepton + jets final state. The search is performed using a data set of $\mathrm {p}$ $\mathrm {p}$ collisions at a centre-of-mass energy of 13 $\,\text {TeV}$ corresponding to an integrated luminosity of $35.9{\,\text {fb}^{-1}} $ as recorded by the CMS experiment at the CERN LHC in the year 2016. The analysis is optimised for final states arising from the $\text {T} $ decay modes to a top quark and a Higgs or $\mathrm {Z}$ boson ( $\text {T} \rightarrow \mathrm {H} \mathrm {t}, \mathrm {Z} \mathrm {t}$ ). The event selection makes use of resolved and merged top quark decay products, as well as decays of boosted Higgs bosons and $\mathrm {Z}$ and $\mathrm {W}$ bosons using jet substructure techniques. No significant deviation from the standard model background expectation is observed. Exclusion limits on the product of the cross section and branching fraction for $\mathrm {Z}'\rightarrow \mathrm {t}\text {T}, \text {T} \rightarrow \mathrm {H} \mathrm {t}, \mathrm {Z} \mathrm {t}, \mathrm {W}\mathrm {b}$ are presented for various combinations of the $\mathrm {Z}'$ resonance mass and the vector-like $\text {T} $ quark mass. These results represent the most stringent limits to date for the decay mode $\mathrm {Z}'\rightarrow \mathrm {t}\text {T} \rightarrow \mathrm {t}\mathrm {H} \mathrm {t}$ . In a benchmark model with extra dimensions, invoking a heavy spin-1 resonance $\mathrm {G}^* $ , masses of the $\mathrm {G}^* $ between 1.5 and 2.3 $\,\text {TeV}$ and between 2.0 and 2.4 $\,\text {TeV}$ are excluded for $\text {T} $ masses of 1.2 and 1.5 $\,\text {TeV}$ , respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

Measurements of Higgs boson production via gluon–gluon fusion and vector-boson fusion using $H\rightarrow WW^*\rightarrow \ell \nu \ell \nu$ decays in pp collisions with the ATLAS detector and their effective field theory interpretations

Higgs boson production cross-sections via gluon–gluon fusion and vector-boson fusion in proton–proton collisions are measured in the $H\rightarrow WW^*\rightarrow \ell \nu \ell \nu$ decay channel. The Large Hadron Collider delivered proton–proton collisions at a centre-of-mass energy of 13 TeV between 2015 and 2018, which were recorded by the ATLAS detector, corresponding to an integrated luminosity of $140\,\text {fb}^{-1}.$ The total cross-sections for Higgs boson production by gluon–gluon fusion and vector-boson fusion times the $H\rightarrow WW^*$ branching ratio are measured to be $12.4^{+1.3}_{-1.2}\,\text {pb}$ and $0.79^{+0.18}_{-0.16}\,\text {pb},$ respectively, in agreement with the Standard Model predictions. Higgs boson production is further characterised through measurements of Simplified Template Cross-Sections in a total of fifteen kinematic fiducial regions. A new scheme of kinematic fiducial regions has been introduced to enhance the sensitivity to CP-violating effects in Higgs boson interactions. Both schemes are used to constrain CP-even and CP-odd dimension-six operators in the Standard Model effective field theory.

Aad, G. [CPPM, Aix-Marseille Université, CNRS/IN2P↗
DOE OSTI2026

VECTOR Phase 1 Dataset: CAV Trajectory and Energy Consumption Records

This dataset contains benchmark experimental data from Phase 1 of the VECTOR project, focusing on the energy impact of CAV hardware components. The dataset includes vehicle trajectory data (speed and position) and corresponding energy consumption records collected from a CAV platform equipped with lidar, cameras, onboard computation units, and communication modules. The primary objective is to quantify the baseline energy consumption attributable to sensing and computing systems, independent of any advanced cooperative control strategies. During experiments, the leading vehicle followed a predetermined velocity profile, and the following CAV mirrored this trajectory using a basic car-following control to ensure consistent driving behavior. This setup enables a reliable benchmark for assessing the energy cost introduced by onboard CDA hardware (e.g., lidar and GPU-based processing). The dataset is essential for evaluating energy baselines and supports future comparative studies involving additional cooperative strategies. ![system img](system.png) ![vector img](vector.png)

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2017

Search for pair production of heavy vector-like quarks decaying to high- p m a t h r m T W bosons and b quarks in the lepton-plus-jets final state in p p collisions at s =13 TeV with the ATLAS detector

CERN-LHC, ATLAS. Limits on pair production of a heavy vector-like T quark together with its antiparticle, where the T quark decays to a W boson and a b quark. The search is based on 36.1 +\- 1.2 fb^{-1} of pp collisions at sqrt{s} = 13 TeV recorded in 2015 and 2016 with the ATLAS detector at the CERN Large Hadron Collider. Data are analysed in the lepton plus jets final state, including at least one b-tagged jet and a large-radius jet identified as originating from the hadronic decay of a high-momentum W boson. The search is also sensitive to a heavy vector-like B quark, in particular in the decay to Wt and the results are thus reinterpreted to provide limits on the B mass. Mass limits on both T and B production are also set as a function of the decay branching ratios.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2016

Measurement of polarization observables in vector meson photoproduction using a transversely-polarized frozen-spin target and polarized photons at CLAS, Jefferson Lab

The study of baryon resonances provides a deeper understanding of the strong interaction because the dynamics and relevant degrees of freedom hidden within them are re ected by the properties of the excited states of baryons. Higher-lying excited states at and above 1.7 GeV/c 2 are generally predicted to have strong couplings to final states involving a heavier meson, e. g. one of the vector mesons, ρ, ω φ, as compared to a lighter pseudoscalar meson, e. g. π and η. Decays to the ππΝ final states via πΔ also become more important through the population of intermediate resonances. We observe that nature invests in mass rather than momentum. The excited states of the nucleon are usually found as broadly overlapping resonances which may decay into a multitude of final states involving mesons and baryons. Polarization observables make it possible to isolate single resonance contributions from other interference terms. The CLAS g9 (FROST) experiment, as part of the N* spectroscopy program at Jefferson Laboratory, accumulated photoproduction data using circularly- & linearly-polarized photons incident on a transversely-polarized butanol target (g9b experiment) in the photon energy range 0:3-2:4 GeV & 0:7-2:1 GeV, respectively. In this work, the analysis of reactions and polarization observables which involve two charged pions, either in the fully exclusive reaction γρ -> ρπ+π- or in the semi-exclusive reaction with a missing neutral pion, γρ -> ρπ + π - (π 0 ) will be presented. For the reaction ρπ + π - , eight polarization observables (I s , I c , P x , P y , $P^s_{x;y}$, $P^c_{x; y}$) have been extracted. The high statistics data rendered it possible to extract these observables in three dimensions. All of them are first-time measurements. The fairly good agreement of Is, Ic obtained from this analysis with the experimental results from a previous CLAS experiment provides support for the first-time measurements. For the reaction γρ -> ρω -> ρπ + π(π 0 , five polarization observables (T, Σ, F, H, P) have been extracted, four of which are first-time measurements at all energies. This analysis thus represents a comprehensive program on vector-meson photoproduction: The ω is observed and studied directly from the data and the polarization observables for the (broad) ω can be extracted from the double-pion reaction in a partial-wave analysis. The 13 polarization observables extracted in this analysis substantially augment the world database of polarization observables for these reactions and are expected to play a crucial role in identifying the contributing baryon resonances.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2017

Optimizing the Performance of Sparse-Matrix Vector Products on Next-Generation Processors

Matrix-vector products are ubiquitous in high-performance scientific applications and have a growing set of occurrences in advanced data analysis activities. Achieving high performance for these kernels is therefore paramount, in part, because these operations can consume vast amounts of application execution time. In this report we document the development of several sparse-matrix vector product kernel implementations using a variety of programming models and approaches. Each kernel is run on a broad set of matrices selected to demonstrate the wide variety of matrix structure and sparsity that is possible with a single, generic kernel. For benchmarking and performance analysis, we utilize leading computing architectures for the NNSA/ASC program including Intel's Knights Landing processor and IBM's POWER8.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Vector Calibration for Vertical Tests of Superconducting RF Cavities

We propose procedure for vector calibration of Q 0 vs E acc curve measurement for superconducting resonators. The proposed vector calibration procedure and hardware has several advantages over the techniques currently used for vertical cavity tests. It provides high level of automation and reduces manpower and preparation time for the test; it provides in situ, real time control of hardware parameters and allows to detect hardware failure and operator's errors; it allows to control and exclude the most significant systematic uncertainties, measured values of Q 0 (E acc ) can be made traceable to national standards.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Updates to Relevance Vector Machine: Multiclass Classification, Variable Selection, and Proof-of-Concept Application to Safeguards Fresh Fuel Verification using List-Mode Neutron Collar Data

To expand the capabilities of safeguards authorities to verify the integrity of fresh fuel assemblies, Oak Ridge National Laboratory has retrofit the existing electronics of the JCC-71 uranium neutron coincidence collar, which contains 18 3 He neutron detectors and an external 241 AmLi(α, n) neutron interrogation source arranged to surround a fresh nuclear fuel assembly. The new electronics system allows analysts to record list-mode neutron multiplicity data in addition to the singles and doubles rates that are currently measured. Based on previous proof-of-concept research, analysis of these new data will identify off-normal fuel configurations in an assembly and characterize or localize the specific partial fuel defects. The purpose of this report it to document the analysis algorithm development and then to demonstrate its capability for the safeguards verification of fresh fuel assemblies using list mode neutron collar data. To analyze the complex list-mode data collected with the upgraded uranium neutron collar, multivariate classification algorithms are being developed using a novel classification method, the relevance vector machine. This approach may be applied to multiclass problems to estimate the probability that test data belongs to one of many possible classes of data. In addition, our method identifies the most useful variables/channels for making predictions, which illuminates the basis for the model’s predictions, and this interpretability is largely unique among data analytics methods. Variable selection occurs during model training and parameter tuning and does not need any external hyperparameter tuning routines. Finally, we apply the modified relevance vector machine to a simulated dataset of list-mode neutron collar data generated with the radiation transport code MCNP. The method can correctly identify off-normal fuel configurations, categorize the data according to four fuel defect scenarios, and rank the channels in the data according to prediction utility. For nuclear safeguards applications, it is concluded that this method has the potential to increase the sensitivity and reliability to detect missing fuel rods from a standard 17 x 17 Pressurized Water Reactor (PWR) fresh fuel assembly. Within this analysis, “off-normal” (i.e., missing fuel rods) were correctly classified in 17 simulated test scenarios with one quarter (25%) of the fresh fuel rods missing using a training data set of 58 simulated measurements.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

Search for New Bosons in Gluon-Gluon and Vector Boson Fusion Processes at the LHC and Development of Silicon Module Assembly Techniques for the CMS High Granularity Calorimeter

A search for heavy resonances decaying to a pair of vectors bosons is presented which utilizes events in which a hadronically decaying Z or W boson is identified using jet substructure techniques and large missing transverse momentum is found. Data analyzed were recorded by the Compact Muon Solenoid experiment at the CERN Large Hadron Collider in 2016, 2017, and 2018, and correspond to 137 fb$^{-1}$ . The events are categorized as having arisen from Vector Boson Fusion process or not, and are characterized by their transverse mass distribution. The standard model backgrounds are estimated based on observed yields in control regions. No excess of events above the expected SM background are observed and limits are placed on the production cross section of Radion (spin-0), Wprime (spin-1) and Bulk graviton (spin2) particles. In adiditon, the high luminosity LHC and the CMS HGCAL upgrade are also presented. The assembly techniques and various tests for the Silicon module and the cassette are discussed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Vectorization of Dynamic Subgraphs via Generative Models (Final Report)

An important class of data analysis tasks stem from comparing subsets of connected records within massive sets of complex relational data. A common approach is to represent each set of connected records with a small graph, or set of data entities (graph vertices) and their relationships (graph edges), and efficient methods to gauge similarity for pairs of graphs are of high interest. This project concentrated on dynamic graphs, where each edge record has an associated timestamp denoting the time of observation. Pre-existing techniques for comparing dynamic graphs concentrate on either computing graph edit distance (number of vertex and edge deletion, addition, and timestamp modifications) or vectorizing the graph with counts of a limited set of dynamic graph motifs (tiny fundamental subgraphs) and computing distances between the vectors. These approaches are less able to see similarities in graphs that are fairly different in size but come from identical graph generation processes. The motif counting approach can be improved for graphs from the same process, but suffers from requiring many types of motifs meaning it is expensive. Moreover, many motifs are not present for small graphs, meaning realizing a a much larger graph came from the same process is difficult.

97 MATHEMATICS AND COMPUTING↗