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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 847 records · Page 47
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

TREAT Neutronics Analysis and Design Support, Part I: Multi-SERTTA

Experiment vehicle design is necessary in preparation for Transient Reactor Test (TREAT) facility restart and the resumption of transient testing to support Accident Tolerant Fuel (ATF) characterization and other future fuels testing requirements. Currently the most mature vehicle design is the Multi-SERTTA (Static Environments Rodlet Transient Test Apparatuses), which can accommodate up to four concurrent rodlet-sized specimens under separate environmental conditions. Robust test vehicle design requires neutronics analyses to support design development, optimization of the power coupling factor (PCF) to efficiently maximize energy generation in the test fuel rodlets, and experiment safety analyses. Calculations were performed to support analysis of a near-final design of the Multi-SERTTA vehicle, the design process for future TREAT test vehicles, and establish analytical practices for upcoming transient test experiments. Models of the Multi-SERTTA vehicle containing typical PWR-fuel rodlets were prepared and neutronics calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries. Calculation of the PCF for reference conditions of a PWR fuel rodlet in clean water at operational temperature and pressure provided results between 1.10 and 1.74 W/g-MW depending on the location of the four Multi-SERTTA units with the stack. Basic changes to the Multi-SERTTA secondary vessel containment and support have minimal impact on PCF; using materials with less neutron absorption can improve expected PCF values, especially in the primary containment. An optimized balance is needed between structural integrity, experiment safety, and energy deposition in the experiment. Type of medium and environmental conditions within the primary vessel surrounding the fuel rodlet can also have a significant impact on resultant PCF values. The estimated reactivity insertion worth into the TREAT core is impacted more by the primary and secondary Multi-SERTTA vehicle structure with the experiment content and contained environment having a near negligible impact on overall system reactivity. Additional calculations were performed to evaluate the peak-to-average assembly powers throughout the TREAT core, as well as the nuclear heat generation for the various structural components of the Multi-SERTTA assembly. Future efforts include the evaluation of flux collars to shape the PCF for individual Multi-SERTTA units during an experiment such as to achieve uniformity in test unit environmental conditions impacted by the non-uniform axial flux/power profile of TREAT. Upon resumption of transient testing, experimental results from both the Multi-SERTTA and Multi-SERTTA-CAL will be compared against calculational results and methods for further optimization and design strategies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2016

TREAT neutronics analysis and design support, Part I: Multi-SERTTA

Experiment vehicle design is necessary in preparation for Transient Reactor Test (TREAT) facility restart and the resumption of transient testing to support Accident Tolerant Fuel (ATF) characterization and other future fuels testing requirements. Currently the most mature vehicle design is the Multi-SERTTA (Static Environments Rodlet Transient Test Apparatuses), which can accommodate up to four concurrent rodlet-sized specimens under separate environmental conditions. Robust test vehicle design requires neutronics analyses to support design development, optimization of the power coupling factor (PCF) to efficiently maximize energy generation in the test fuel rodlets, and experiment safety analyses. Calculations were performed to support analysis of a near-final design of the Multi-SERTTA vehicle, the design process for future TREAT test vehicles, and establish analytical practices for upcoming transient test experiments. Models of the Multi-SERTTA vehicle containing typical PWR-fuel rodlets were prepared and neutronics calculations were performed using MCNP6.1 with ENDF/B-VII.1 nuclear data libraries. Calculation of the PCF for reference conditions of a PWR fuel rodlet in clean water at operational temperature and pressure provided results between 1.10 and 1.73 W/g-MW depending on the location of the four Multi-SERTTA units with the stack. Basic changes to the Multi-SERTTA secondary vessel containment and support have minimal impact on PCF; using materials with less neutron absorption can improve expected PCF values, especially in the primary containment. An optimized balance is needed between structural integrity, experiment safety, and energy deposition in the experiment. Type of medium and environmental conditions within the primary vessel surrounding the fuel rodlet can also have a significant impact on resultant PCF values. The estimated reactivity insertion worth into the TREAT core is impacted more by the primary and secondary Multi-SERTTA vehicle structure with the experiment content and contained environment having a near negligible impact on overall system reactivity. Additional calculations were performed to evaluate the peak-to-average assembly powers throughout the TREAT core, as well as the nuclear heat generation for the various structural components of the Multi-SERTTA assembly. Future efforts include the evaluation of flux collars to shape the PCF for individual Multi-SERTTA units during an experiment such as to achieve uniformity in test unit environmental conditions impacted by the non-uniform axial flux/power profile of TREAT. Upon resumption of transient testing, experimental results from both the Multi-SERTTA and Multi-SERTTA-CAL will be compared against calculational results and methods for further optimization and design strategies. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

AuPd Nanoicosahedra: Atomic-Level Surface Modulation for Optimization of Electrocatalytic and Photocatalytic Energy Conversion

Modulation of bimetallic nanocatalysts with atomic precision would allow for significant increases in catalyst activity through the optimization of heteroatomic interplay. In practice, this level of control over homogeneously turning the heteroatomic states in the surface regions of catalysts remains a great challenge for practical applications requiring mass production. In this work, a one-step aqueous strategy for preparation of AuPd nanoicosahedra core–shell structures has been developed. By turning the molar ratio of Au and Pd precursors, the nanoicosahedra could be made with uniform core composition (Pd ~20%) and largely flexible surface compositions (Pd: 20–70%). Under model reactions of electrochemical ethanol oxidation (EOR) and 4-nitrophenol (4-NP) reduction, the Au 55 Pd 45 surface displayed superior activities. Here, x-ray absorption spectroscopy revealed that AuPd nanoicosahedra with Pd-poor surfaces (Au 79 Pd 21 and Au 60 Pd 40 ) maintain Au-like electronic structures while those with Pd-rich surfaces are more Pd-like. The Au 55 Pd 45 surface struck a delicate balance between the two extremes, leading to the optimal Au–Pd interplay for catalytic performance. Overall, the development of a one-step aqueous strategy for atomic-level control over bimetallic nanoparticle surface states is an important milestone for future advances in catalysis. Our findings in atomic-scale catalyst design will bring deep insights into the fields of nanosynthesis and heterogeneous catalysis, which will be beneficial for further scientific breakthroughs.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Jagged Tiling for Intra-tile Parallelism and Fine-Grain Multithreading

In this paper, we have developed a novel methodology that takes into consideration multithreaded many-core designs to better utilize memory/processing resources and improve memory residence on tileable applications. It takes advantage of polyhedral analysis and transformation in the form of PLUTO, combined with a highly optimized finegrain tile runtime to exploit parallelism at all levels. The main contributions of this paper include the introduction of multi-hierarchical tiling techniques that increases intra tile parallelism; and a data-flow inspired runtime library that allows the expression of parallel tiles with an efficient synchronization registry. Our current implementation shows performance improvements on an Intel Xeon Phi board up to 32.25% against instances produced by state-of-the-art compiler frameworks for selected stencil applications.

compiler↗
DOE OSTI2015

The effect of morphology and confinement on the high-pressure phase transition in ZnO nanostructure

The transition pressure (P{sub t}) of the B4-to-B1 phase transformation of zinc oxide nanoparticle (n-ZnO) structures was investigated in terms of their size and morphology. Nanorods, nanopencils, nanopyramids, nanowires, and nanotubes of the B4 phase in various sizes were directly built up by accounting for the atomic basis of the core and surface regions. The previously proposed transformation path was performed for constructing shapes and sizes compatible with B1 phases. Using systematic density functional theory, the surfaces were cleaved from the optimized crystal structures at different pressures in both the B4 and B1 phases. A method for calculating the surface energy at different pressures is proposed using an asymmetric slab model. Using the proposed model, the transition pressure of n-ZnO structures was found to significantly depend on their morphology and size, which is in good agreement with the available experimental reports.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2016

Imaging crystal spectrometer for high-resolution x-ray measurements on electron beam ion traps and tokamaks

Here, we describe a crystal spectrometer implemented on the Livermore electron beam ion traps that employ two spherically bent quartz crystals and a cryogenically cooled back-illuminated charge-coupled device detector to measure x rays with a nominal resolving power of λ/Δλ ≥ 10 000. Its focusing properties allow us to record x rays either with the plane of dispersion perpendicular or parallel to the electron beam and, thus, to preferentially select one of the two linear x-ray polarization components. Moreover, by choice of dispersion plane and focussing conditions, we use the instrument either to image the distribution of the ions within the 2 cm long trap region, or to concentrate x rays of a given energy to a point on the detector, which optimizes the signal-to-noise ratio. We demonstrate the operation and utility of the new instrument by presenting spectra of Mo 34+ , which prepares the instrument for use as a core impurity diagnostic on the NSTX-U spherical torus and other magnetic fusion devices that employ molybdenum as plasma facing components.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2018

Parallel k-means Clustering of Geospatial Data Sets Using Manycore CPU Architectures

The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery and mining of weather, climate, ecological, and other geoscientific data sets fused from disparate sources. Many of the standard tools used on individual workstations are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of parallelism available in state-of-the-art high-performance computing platforms can enable such analysis. Here, we describe pKluster, an open-source tool we have developed for accelerated k-means clustering of geospatial and geospatiotemporal data, and discuss algorithmic modifications and code optimizations we have made to enable it to effectively use parallel machines based on novel CPU architectures—such as the Intel “Knights Landing” Xeon Phi and Skylake Xeon processors—with many cores and hardware threads, and employing significant single instruction, multiple data (SIMD) parallelism. We outline some applications of the code in ecology and climate science contexts and present a detailed discussion of the performance of the code for one such application, LiDAR-derived vertical vegetation structure classification.

Mills, Richard T↗
DOE OSTI2016

Structures and magnetic properties of Ni n (n = 36-40) clusters from first-principles calculations

A genetic algorithm (GA) coupled with a tight-binding (TB) interatomic potential is used to search for the low-energy structures of medium-sized Ni n (n = 36-40) clusters. Structural candidates obtained from our GA search are further optimized with first-principles calculations. The medium-sized nickel clusters ranging from 36 to 40 atoms are found to favor the double-icosahedron-based structures with a Ni7 core (a pentagonal bipyramidal structure) except Ni38 cluster. The lowest-energy structure of Ni38 can be considered to be a magic cluster, which is a typical face-centered cubic structure with large stability and magnetic moment.

Song, W.↗
DOE OSTI2019

Reverse-Mode Algorithmic Differentiation of an OpenMP-Parallel Compressible Flow Solver

y Reverse-mode algorithmic differentiation (AD) is an established method for obtaining adjoint derivatives of computer simulation applications. In computational fluid dynamics (CFD), adjoint derivatives of a cost function output such as drag or lift with respect to design parameters such as surface coordinates or geometry control points are a key ingredient for shape optimization, uncertainty quantification and flow control. The computational cost of CFD applications and their derivatives makes it essential to use high-performance computing hardware efficiently, including multi- and many-core architectures. Nevertheless, OpenMP is not supported in most AD tools, and previously shown methods achieve poor scalability of the derivative code. We present the AD of an OpenMP-parallelized finite volume compressible flow solver for unstructured meshes. Our approach enables us to reuse the parallelization of the original code in the computation of adjoint derivatives. The method works by identifying code segments that can be differentiated in reverse-mode without changing their memory access pattern. The OpenMP parallelization is integrated into the derivative code during the build process in a way that is robust to modifications of the original code and independent of the OpenMP support of the differentiation tool. We show the scalability of our adjoint CFD solver on test cases ranging from thousands to millions of finite volume mesh cells on CPUs with up to 16 threads as well as on an Intel XeonPhi card with 236 threads. We demonstrate that our approach is more practical to implement for production-sized CFD codes and produces more efficient adjoint derivative code than previously shown AD methods.

Huckelheim, Jan↗
DOE OSTI2021

Theoretically and practically efficient parallel nucleus decomposition

This paper studies the nucleus decomposition problem, which has been shown to be useful in finding dense substructures in graphs. We present a novel parallel algorithm that is efficient both in theory and in practice. Our algorithm achieves a work complexity matching the best sequential algorithm while also having low depth (parallel running time), which significantly improves upon the only existing parallel nucleus decomposition algorithm (Sariyüce et al. , PVLDB 2018). The key to the theoretical efficiency of our algorithm is a new lemma that bounds the amount of work done when peeling cliques from the graph, combined with the use of a theoretically-efficient parallel algorithms for clique listing and bucketing. We introduce several new practical optimizations, including a new multi-level hash table structure to store information on cliques space-efficiently and a technique for traversing this structure cache-efficiently. On a 30-core machine with two-way hyper-threading on real-world graphs, we achieve up to a 55x speedup over the state-of-the-art parallel nucleus decomposition algorithm by Sariyüce et al. , and up to a 40x self-relative parallel speedup. We are able to efficiently compute larger nucleus decompositions than prior work on several million-scale graphs for the first time.

Computer Science↗
DOE OSTI2016

Final Report for DoE Grant DE-SC-0011689 - Studies of Particle Astrophysics at the Cosmic Frontier

Our research focuses on the “Cosmic Frontier”, one of the three principle thrusts of the DoE Office of Science High Energy Physics research program. The 2013 community summer study “Snowmass on the Mississippi” catalyzed joint work to describe the status and future prospects of this research thrust. Over its history, the field of cosmic ray studies has provided many discoveries of central importance to the the progress of high energy physics, including the identification of new elementary particles, measurements of particle interactions far above accelerator energies, and the confirmation of neutrino oscillations. In our research we continued this tradition, employing 2 instruments (the Auger Observatory and the HAWC Observatory) to study high energy physics questions using cosmic rays. One approach to addressing particle physics questions at the cosmic frontier is to study the very highest energy cosmic rays. This has been the major thrust of our research effort. The two largest currently operating ultra-high energy cosmic ray (UHECR) observatories are the Pierre Auger Observatory in the Southern hemisphere, covering an area of 3000 km 2 and the Telescope Array (TA) in the Northern hemisphere, covering about 700 km 2 . The observatories sample the cosmic ray air showers at ground level (with 1660 water Cerenkov stations in the Auger surface detector), and also measure the longitudinal development of air showers on clear moonless nights (approx. 10% of the events) using atmospheric fluorescence detectors. The observatories have recently installed low energy extensions, which provide an overlap with the LHC energy regime. The Auger and TA teams have established joint working groups to discuss experimental methods, compare data analyses and modeling, and perform cross calibrations. Another approach is to study high energy gamma rays. The High Altitude Water Cerenkov (HAWC) gamma-ray observatory is located at 4100 m above sea level near Pico de Orizaba in central Mexico. HAWC is the most sensitive, wide field of view, TeV gamma-ray observatory in operation. After 4 years of construction, operation of the full detector began in March 2015. The HAWC detector contains 300 tanks each 7.3 m in diameter and 4.5 m deep containing pure water. Each water tank is instrumented with 4 upward-viewing photomultiplier tubes mounted at their bottom. The water tanks record the energy deposited by and arrival times of the constituent components of impinging extensive air showers (EAS). The tanks are close-packed to optimize the spatial sampling of the shower front. The distribution of deposited energy across the shower is used for gamma-hadron rejection. Showers with large energy deposit away from the core are rejected as being hadron-initiated. The detector operates at full efficiency above 3 TeV. The angular resolution above that energy approaches 0.1 degree. As the detector operates both day and night, the wide field of view of ~2 sr, allows ~2/3 of the sky to be observed each day.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Roll-to-Roll Advanced Materials Manufacturing DOE Laboratory Collaboration - FY2018 Final Report

High-value R2R processing is used to support a wide range of products in applications which span many industrial business sectors. The overall R2R process technology can be considered as “mature” as the process methodology and has been in use for decades. This continuous processing technique traditionally involves deposition of material(s) onto moving webs or carriers or other continuous R2R, belt-fed, or conveyor-based processes that enable successive steps to build a final version which serves to support the deposited materials. Current process technologies, which typify “roll to roll”, include tape casting, silk-screen printing, reel-to-reel vacuum deposition/coating and R2R lithography. Products supported by R2R manufacturing include micro-electronics, electro-chromic window films, PVs, fuel cells for energy conversion, battery electrodes for energy storage, and barrier materials. Due to innovation in materials and process equipment, high-quality yet very low-cost multi-layer technologies can be manufactured on a very cost-competitive basis. To move energy-related products from high-cost niche applications to the commercial sector, a means must be available to enable manufacture of these products in a cost-competitive manner that is affordable by the general consumer. Fortunately, products such as fuel cells, thin- and mid-film PVs, batteries, electrochromic and piezoelectric films, water separation membranes, and other energy saving technologies readily lend themselves to manufacture using R2R approaches.Within the DOE EERE AMO, it was recognized that establishment of a program supported at the DOE National Laboratories, along with their immense design of materials and equipment modelling capabilities enabled with use of high-performance computing, could take advantage of available R2R infrastructure to manufacture new technologies. In FY 2016, a R2R Consortium was established and provided with initial “seed” funding to take an approach that was envisioned to be supportable by advanced manufacturing R2R processes. This collaborative approach was designed to foster identification and development of materials and processes related to R2R for clean-energy product development. Using computational and experimental capabilities by acknowledged subject matter experts within the supported National Laboratory system, this collaborative project would leverage the capabilities and expertise at each of four laboratories to further the development of an enabling high-volume cost-competitive platform technology. The collaboration team that is comprised of ORNL, ANL, NREL and LBNL, coordinating with EPB and other selected industry partners, was formed in April 2016 to initially address enhancing battery electrode performance and R2R manufacturing challenges. The research efforts were to predict and measure changes and results in electrode morphology and performance based on process condition changes; to evaluate mixed, active, particle size deposition and drying for novel electrode materials; to model various process condition changes and the resulting morphology and electrode performance; and to develop and validate NDE techniques for in-line measurement of battery electrode material properties. These efforts carried through FY 2017 and completed at the end of FY 2018.The approach was to look at compositions of materials with different particle sizes to make electrode samples using a R2R manufacturing process. The shape, size, and morphology of the materials, the chemistry of the formulation, the nature of slurries, their coating rate, the rate of drying all play a role in determining the final coating architecture, quality, and performance. A commercial cathode material was selected to make a series of cathodes and anodes by single pass, dual pass and slot die methods. Analysis of all the compiled results for this battery electrode development were that the best performing cathodes included: dual-pass electrode with large particles near the foil, mixed small and large particles, and small particles only. Whereas, the best performing anodes were with a mix of small and large graphite particles. An additional core project was added in FY 2017 to conduct studies of fuel cell materials that can be produced using R2R processes. The goal of this project is to explore, understand and optimize material and process parameters to support increased throughput, increased quality, and reduced cost for high volume production of gas-diffusion electrodes (GDEs) for PEMFCs. Project work in FY 2018 were to use a R2R process to fabricate electrodes without ionomer overlayer that can produce the equivalent mass activity as spray-coated electrodes with an ionomer overlayer. Oxygen-limiting current measurements were utilized to optimize oxygen mass transport. Alcohol-rich solvents were investigated, and results were that the alcohol and water ratio can be tuned to control ionomer distribution. Water-rich solvents produce a more dispersed ink which results in better high-current density performance.

36 MATERIALS SCIENCE↗
DOE OSTI2018

End-System Aware Peak Link Utilization Transport for Big Data Transfer over Dedicated Connections

High-performance networks provisioning 10/40-Gbps dedicated channels have been rapidly developed andincreasingly deployed to support big data transfers on the order of terabytes or petabytes in large-scale network-intensiveapplications. However, end users have not seen corresponding increase in application throughput mainly because traditional end-to-end transport methods are not optimized for such connections. New congestion or flow control mechanisms are desirable to meet the challenges brought to transport protocol design by dedicated connections. The advent and proliferation of multi-core processors make it now possible to improve application throughput by providing multiple processing and network resources to a single data transfer. Based on the existing PLUT method, we proposed a new dynamic buffer management scheme and an automatic parallelism tuning mechanism to achieve the maximal bottleneck rate. The performance superiority of PLUT is justified by the experimental results collected over a local 10Gbps dedicated connection.

Rao, Nageswara↗
DOE OSTI2019

Speeding up Particle Track Reconstruction in the CMS Detector using a Vectorized and Parallelized Kalman Filter Algorithm

Building particle tracks is the most computationally intense step of event reconstruction at the LHC. With the increased instantaneous luminosity and associated increase in pileup expected from the High-Luminosity LHC, the computational challenge of track finding and fitting requires novel solutions. The current track reconstruction algorithms used at the LHC are based on Kalman filter methods that achieve good physics performance. By adapting the Kalman filter techniques for use on many-core SIMD architectures such as the Intel Xeon and Intel Xeon Phi and (to a limited degree) NVIDIA GPUs, we are able to obtain significant speedups and comparable physics performance. New optimizations, including a dedicated post-processing step to remove duplicate tracks, have improved the algorithm's performance even further. Here we report on the current structure and performance of the code and future plans for the algorithm.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

Low level coupling scheme between neutronics and thermal-hydraulics based on Anderson acceleration

The simulation of nuclear reactors is a multiphysics problem mixing, amongst other fields, neutron transport and thermal-hydraulics. The simplest and most used approach in multiphysics simulation is based on the coupling of single-physics codes in a black-box fashion. However, in order to reduce the computational time needed for such simulations, case-dependent optimizations are often required. In this paper, we aim at reducing the computational time required to solve a coupled neutronic/thermal-hydraulic steady-state problem on a simplified Pressurized Water Reactor (PWR) core. The idea is to deal simultaneously with the coupling of the energy groups of the deterministic neutronic description of the core and its thermal-hydraulic description with the Anderson acceleration. By doing so, the fission source terms are directly accelerated instead of the power map as done in most cases. The power method used to solve the k-eigenvalue problem inside the neutronic solver is thus accelerated with the Anderson acceleration. The numerical experimentations conducted in this work are performed using APOLLO3 and THEDI, and indicate that such coupling strategy improves the convergence rates in terms of number of iterations required and the total computational time. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Intelligent Experiments through Real-Time AI: Fast Data Processing and Autonomous Detector Control for High-Energy Nuclear Experiments

The aim of this project is to develop software and hardware for fast real-time data processing and autonomous detector control and calibration for the sPHENIX and the future EIC experiments. Below summarizes Georgia Tech team efforts in the past year: 1. We developed a real-time clustering algorithm and FPGA-based pipeline architecture for processing fired pixel data from ALPIDE sensors in sPHENIX experiments. Our Columnar Clustering Co-Design introduces a hardware-aware, stream-friendly approach that segments pixel data by column pairs using a Column Pair Clustering (CPC) strategy, followed by Cluster Stitching to merge adjacent subclusters. Implemented in Vitis HLS, the pipeline comprises five stages—read-in, subclustering, stitching, analysis, and write-out—connected by tagged HLS streams with custom end-of-event signaling for robust synchronization. We designed a pipelined dataflow model optimized for throughput, low latency, and minimal buffering, enabling scalable clustering across events of arbitrary size. Our system maintains spatial precision via center-of-mass and shape key extraction and efficiently handles edge cases such as fragmented or nested clusters. Compared against DBSCAN in both software and hardware, our approach demonstrates competitive performance under FPGA constraints. 2. We also conducted a comprehensive algorithm-to-hardware co-design of connected component analysis tailored for sPHENIX experiments, focusing on real-time, low-latency processing using FPGAs and High-Level Synthesis (HLS). Starting from a Python-based particle tracking pipeline, the team translated the core logic—graph traversal via DFS and Union-Find—into an HLS-compatible C++ model, replacing dynamic memory and recursion with static arrays and pipelined control flow. The final design includes a fully streamed and dataflow-compatible Union-Find kernel optimized across five iterations, incorporating loop pipelining, array partitioning, AXI/FIFO interface tuning, and function flattening. Experimental results show up to 14.8× speedup over the CPU baseline, reducing per-graph latency to 1.58 μs and demonstrating strong resource efficiency with only ~7k LUTs and zero BRAM usage. The design maintains functional correctness against the Python reference using a Python-based C-simulation framework and Mean Squared Error metrics. This work validates the potential of HLS-driven FPGA designs for edge-level HEP data acquisition, laying a scalable foundation for future integration with real-time detector pipelines and multi-graph processing systems.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Stepwise Dynamic Calibration of a Hydromechanical Simulation Using Time-Lapse Vertical Seismic Profile

This study aims to develop a methodology for calibrating subsurface stress changes through time-lapse Vertical Seismic Profiling (VSP) integration. The selected study site is the 13-10A injector well within the ongoing CO2-EOR operation of the Farnsworth Field Unit. The Time-lapse VSP dataset carries the combined effects of fluid substitution and mean effective stress changes, thereby providing a dataset amenable for the calibration of production and injection-induced stress changes. The concept is similar to calibrating a reservoir simulation model in that the process honor real field data to set up an inverse problem. The solution optimizes the independent and impactful geomechanical parameters that replicate the observed time-lapse seismic velocity changes. This stress calibration is enabled by 4D geomechanical modeling and the VSP Integration workflow. This calibration benefits from extensive geological, geophysical and geomechanical characterization through 3D seismic data, geophysical well logs, and core assessed as part of the 1D MEM conducted on the 13-10A subject well. These data are used to develop a site-specific rock physics model. The Biot Gassmann workflow combines rock physics and reservoir simulation outputs to determine the fluid substitution contribution to seismic velocity change. Additionally, modeled seismic velocity attributed to mean effective stress are determined from the geomechanical simulation outputs, and the stress-velocity relationship developed from the ultrasonic seismic velocity measurements on the extracted Morrow B core. A penalty function is then formed between the modeled seismic velocities and the observed time-lapse VSP dataset. Four independent and impactful geomechanical parameters have been determined. These are the bulk modulus and shear modulus for zero porosity and the shear and compressional seismic velocity to mean effective stress derivatives. The dataset of numerous coupled hydromechanical- geomechanical simulation realizations is built by combining variations of the four stated geomechanical parameters. A machine learning-assisted workflow comprised of an artificial neural network and a particle swarm optimizer are used to converge on the optimal geomechanical parameters. The successful execution of this workflow has affirmed the suitability of acoustic time-lapse measurements for 4D-VSP geomechanical stress calibration pending measurable stress sensitivities within the anticipated effective stress changes and the availability of suitable and reliable datasets for petroelastic modeling.

02 PETROLEUM↗
DOE OSTI2019

The Effect of Ring Expansion in Thienobenzo[ b ]indacenodithiophene Polymers for Organic Field-Effect Transistors

A fused donor, thienobenzo[b]indacenodithiophene (TBIDT), was designed and synthesized using a novel acid-promoted cascade ring closure strategy, and then copolymerized with a benzothiadiazole (BT) monomer. The backbone of TBIDT is an expansion of the well-known indacenodithiophene (IDT) unit and was expected to enhance the charge carrier mobility by improving backbone planarity and facilitating short contacts between polymer chains. However, the optimized field-effect transistors demonstrated an average saturation hole mobility of 0.9 cm 2 V -1 s -1 , lower than the performance of IDT-BT (~1.5 cm 2 V -1 s -1 ). Mobilities extracted from time-resolved microwave conductivity measurements were consistent with the trend in hole mobilities in organic field-effect transistor devices. Scanning tunneling microscopy measurements and computational modeling illustrated that TBIDT-BT exhibits a less ordered microstructure in comparison to IDT-BT. This reveals that a regular side-chain packing density, independent of conformational isomers, is critical to avoid local free volume due to irregular packing, which can host trapping impurities. DFT calculations indicated that TBIDT-BT, despite containing a larger, planar unit, showed less stabilization of planar backbone geometries in comparison to IDT-BT. This is due to the reduced electrostatic stabilizing interactions between the peripheral thiophene of the fused core and the BT unit, resulting in a reduction of the barrier to rotation around the single bond. Finally, these insights provide a greater understanding of the general structure-property relationships required for semiconducting polymer repeat units to ensure optimal backbone planarization, as illustrated with IDT-type units, guiding the design of novel semiconducting polymers with extended fused backbones for high-performance field-effect transistors.

36 MATERIALS SCIENCE↗