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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A modular chromosomally integrated toolkit for ectopic gene expression in Vibrio cholerae

The ability to express genes ectopically in bacteria is essential for diverse academic and industrial applications. Two major considerations when utilizing regulated promoter systems for ectopic gene expression are (1) the ability to titrate gene expression by addition of an exogenous inducer and (2) the leakiness of the promoter element in the absence of the inducer. Here, we describe a modular chromosomally integrated platform for ectopic gene expression in Vibrio cholerae . We compare the broadly used promoter elements P tac and P BAD to versions that have an additional theophylline-responsive riboswitch (P tac -riboswitch and P BAD -riboswitch). These constructs all exhibited unimodal titratable induction of gene expression, however, max induction varied with P tac > P BAD > P BAD -riboswitch > P tac -riboswitch. We also developed a sensitive reporter system to quantify promoter leakiness and show that leakiness for P tac > P tac -riboswitch > P BAD ; while the newly developed P BAD -riboswitch exhibited no detectable leakiness. We demonstrate the utility of the tightly inducible P BAD -riboswitch construct using the dynamic activity of type IV competence pili in V. cholerae as a model system. The modular chromosomally integrated toolkit for ectopic gene expression described here should be valuable for the genetic study of V. cholerae and could be adapted for use in other species.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Fast correlation function calculator: A high-performance pair-counting toolkit

A novel high-performance exact pair-counting toolkit called fast correlation function calculator (FCFC) is presented. With the rapid growth of modern cosmological datasets, the evaluation of correlation functions with observational and simulation catalogues has become a challenge. High-efficiency pair-counting codes are thus in great demand. We introduce different data structures and algorithms that can be used for pair-counting problems, and perform comprehensive benchmarks to identify the most efficient algorithms for real-world cosmological applications. We then describe the three levels of parallelisms used by FCFC, SIMD, OpenMP, and MPI, and run extensive tests to investigate the scalabilities. Finally, we compare the efficiency of FCFC with alternative pair-counting codes. The data structures and histogram update algorithms implemented in FCFC are shown to outperform alternative methods. FCFC does not benefit greatly from SIMD because the bottleneck of our histogram update algorithm is mainly cache latency. Nevertheless, the efficiency of FCFC scales well with the numbers of OpenMP threads and MPI processes, even though speedups may be degraded with over a few thousand threads in total. FCFC is found to be faster than most (if not all) other public pair-counting codes for modern cosmological pair-counting applications.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

CMS Experience with Adoption of the Community supported DD4hep Toolkit

DD4hep is an open-source software toolkit that provides comprehensive and complete generic detector descriptions for high energy physics (HEP) detectors. The Compact Muon Solenoid collaboration (CMS) has recently evaluated and adopted DD4hep to replace its custom detector description software. CMS has demanding software requirements as a very large, longrunning experiment that must support legacy geometries and study many possible upgraded detector designs of a constantly evolving detector that will be taking data for many years to come. CMS has chosen DD4hep since it is a high-quality, community-supported solution that will benefit from continuing modernization and maintenance. This presentation will discuss the issues of DD4hep adoption, the advantages and disadvantages of the various design choices, performance results, and the integration of the plugin systems from CMS and Gaudi, another open-source software framework. Recommendations about DD4hep based upon the CMS use cases will also be presented.

Vuosalo, Carl↗
DOE OSTI2021

Evaluation of Portable Acceleration Solutions for LArTPC Simulation Using Wire-Cell Toolkit

The Liquid Argon Time Projection Chamber (LArTPC) technology plays an essential role in many current and future neutrino experiments. Accurate and fast simulation is critical to developing efficient analysis algorithms and precise physics model projections. The speed of simulation becomes more important as Deep Learning algorithms are getting more widely used in LArTPC analysis and their training requires a large simulated dataset. Heterogeneous computing is an efficient way to delegate computationally intensive tasks to specialized hardware. However, as the landscape of compute accelerators quickly evolves, it becomes increasingly difficult to manually adapt the code to the latest hardware or software environments. A solution which is portable to multiple hardware architectures without substantially compromising performance would thus be very beneficial, especially for long-term projects such as the LArTPC simulations. In search of a portable, scalable and maintainable software solution for LArTPC simulations, we have started to explore high-level portable programming frameworks that support several hardware backends. In this paper, we present our experience porting the LArTPC simulation code in the Wire-Cell Toolkit to NVIDIA GPUs, first with the CUDA programming model and then with a portable library called Kokkos. Preliminary performance results on NVIDIA V100 GPUs and multi-core CPUs are presented, followed by a discussion of the factors affiecting the performance and plans for future improvements.

Yu, Haiwang↗
DOE OSTI2025

Computational toolkit for predicting thickness of 2D materials using machine learning and autogenerated dataset by large language model

The thickness of 2D materials not only plays a crucial role in determining the performance of nanoelectronic and optoelectronic devices but also introduces complexities in predicting volume-dependent properties, such as energy storage capacity, due to the intrinsic vacuum within these materials. Although a plethora of experimental techniques, including but not limited to optical contrast, Raman spectroscopy, nonlinear optical spectroscopy, near-field optical imaging, and hyperspectral imaging, facilitate the measurement of 2D material thickness, comprehensive data for many materials remain elusive. Over the past decade, the exponential proliferation of 2D materials and their heterostructures has outstripped the capabilities of conventional experimental and computational approaches. In this evolving landscape, machine learning (ML) has emerged as an indispensable tool, offering a scalable approach to augment these traditional methodologies. Addressing the critical gap, we introduce THICK2D—Thickness Hierarchy Inference and Calculation Kit for 2D Materials. This Python-based computational framework harnesses an autogenerated thickness database, developed using large language models, and advanced ML algorithms to facilitate the rapid and scalable estimation of material thickness, relying solely on crystallographic data. To demonstrate the utility and robustness of THICK2D, we successfully used the toolkit to predict the thickness of more than 8000 2D-based materials, sourced from two extensive 2D materials databases. THICK2D is disseminated as an open-source utility, accessible on GitHub at https://github.com/gmp007/THICK2D, and archived on Zenodo at https://10.5281/zenodo.11216648.

Ekuma, Chinedu E. (ORCID:0000000258527556)↗
DOE OSTI2019

Design and characterization of mutant and wildtype huntingtin proteins produced from a toolkit of scalable eukaryotic expression systems

The gene mutated in individuals with Huntington's disease (HD) encodes the 348-kDa huntingtin (HTT) protein. Pathogenic HD CAG-expansion mutations create a polyglutamine (polyQ) tract at the N terminus of HTT that expands above a critical threshold of ~35 glutamine residues. The effect of these HD mutations on HTT is not well understood, in part because it is difficult to carry out biochemical, biophysical, and structural studies of this large protein. To facilitate such studies, we have generated expression constructs for the scalable production of HTT in multiple eukaryotic expression systems in this work. Our set of HTT expression clones comprised both N- and C-terminally FLAG-tagged HTT constructs with polyQ lengths representative of the general population, HD patients, and juvenile HD patients, as well as the more extreme polyQ expansions used in some HD tissue and animal models. Our expression system yielded milligram quantities of pure recombinant HTT protein, including many of the previously mapped post-translational modifications. We characterized both apo and HTT–HTT-associated protein 40 (HAP40) complex samples produced with this HD resource, demonstrating that this toolkit can be used to generate physiologically meaningful HTT complexes. We further demonstrate that these resources can produce sufficient material for protein-intensive experiments, such as small-angle X-ray scattering, providing biochemical insight into full-length HTT protein structure. The work outlined and the tools generated here lay a foundation for further biochemical and structural work on the HTT protein and for studying its functional interactions with other biomolecules.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Geometrical structures for radiation biology research as implemented in the TOPAS-nBio toolkit

Computational simulations, such as Monte Carlo track structure simulations, offer a powerful tool for quantitatively investigating radiation interactions within cells. Additionally, the modelling of the spatial distribution of energy deposition events as well as diffusion of chemical free radical species, within realistic biological geometries, can help provide a comprehensive understanding of the effects of radiation on cells. Track structure simulations, however, generally require advanced computing skills to implement. The TOPAS-nBio toolkit, an extension to TOPAS (TOol for PArticle Simulation), aims to provide users with a comprehensive framework for radiobiology simulations, without the need for advanced computing skills. This includes providing users with an extensive library of advanced, realistic, biological geometries ranging from the micrometer scale (e.g. cells and organelles) down to the nanometer scale (e.g. DNA molecules and proteins). Finally, were we present the geometries available in TOPAS-nBio.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

PyCBC Inference: A Python-based Parameter Estimation Toolkit for Compact Binary Coalescence Signals

We introduce new modules in the open-source PyCBC gravitational-wave astronomy toolkit that implement Bayesian inference for compact-object binary mergers. We review the Bayesian inference methods implemented and describe the structure of the modules. Here, we demonstrate that the PyCBC Inference modules produce unbiased estimates of the parameters of a simulated population of binary black hole mergers. We show that the parameters' posterior distributions obtained using our new code agree well with the published estimates for binary black holes in the first Advanced LIGO–Virgo observing run.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2019

GUNDAM: a toolkit for fast spatial correlation functions in galaxy surveys

ABSTRACT We describe the capabilities of a new software package to calculate two-point correlation functions (2PCFs) of large galaxy samples. The code can efficiently estimate 3D/projected/angular 2PCFs with a variety of statistical estimators and bootstrap errors, and is intended to provide a complete framework (including calculation, storage, manipulation, and plotting) to perform this type of spatial analysis with large redshift surveys. Gundam implements a very fast skip list/linked list algorithm that efficiently counts galaxy pairs and avoids the computation of unnecessary distances. It is several orders of magnitude faster than a naive pair counter, and matches or even surpass other advanced algorithms. The implementation is also embarrassingly parallel, making full use of multicore processors or large computational clusters when available. The software is designed to be flexible, user friendly and easily extensible, integrating optimized, well-tested packages already available in the astronomy community. Out of the box, it already provides advanced features such as custom weighting schemes, fibre collision corrections and 2D correlations. Gundam will ultimately provide an efficient toolkit to analyse the large-scale structure ‘buried’ in upcoming extremely large data sets generated by future surveys.

Donoso, E.↗
DOE OSTI2017

A multi-purpose toolkit to enable advanced genome engineering in plants

Here, we report a comprehensive toolkit that enables targeted, specific modification of monocot and dicot genomes using a variety of genome engineering approaches. Our reagents, based on Transcription Activator-Like Effector Nucleases TALENs and the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 system, are systematized for fast, modular cloning and accommodate diverse regulatory sequences to drive reagent expression. Vectors are optimized to create either single or multiple gene knockouts and large chromosomal deletions. Moreover, integration of geminivirus-based vectors enables precise gene editing through homologous recombination. Regulation of transcription is also possible. A web-based tool streamlines vector selection and construction. One advantage of our platform is the use of the Csy-type (CRISPR system yersinia) ribonuclease 4 Csy4 and tRNA processing enzymes to simultaneously express multiple guide RNAs (gRNAs). For example, we demonstrate targeted deletions in up to six genes by expressing twelve gRNAs from a single transcript. Csy4 and tRNA expression systems are almost twice as effective in inducing mutations as gRNAs expressed from individual RNA polymerase III promoters. Mutagenesis can be further enhanced 2.5-fold by incorporating the Trex2 exonuclease. Finally, we demonstrate that Cas9 nickases induce gene targeting at frequencies comparable to native Cas9 when they are delivered on geminivirus replicons. The reagents have been successfully validated in tomato (Solanum lycopersicum), tobacco (Nicotiana tabacum), Medicago truncatula, wheat (Triticum aestivum), and barley (Hordeum vulgare).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2018

Harnessing the Power of Many: Extensible Toolkit for Scalable Ensemble Applications

Many scientific problems require multiple distinct computational tasks to be executed in order to achieve a desired solution. We introduce the Ensemble Toolkit (EnTK) to address the challenges of scale, diversity and reliability they pose. We describe the design and implementation of EnTK, characterize its performance and integrate it with two exemplar use cases: seismic inversion and adaptive analog ensembles. We perform nine experiments, characterizing EnTK overheads, strong and weak scalability, and the performance of the two use case imple-mentations, at scale and on production infrastructures. We show how EnTK meets the following general requirements: (i) imple-menting dedicated abstractions to support the description and execution of ensemble applications; (ii) support for execution on heterogeneous computing infrastructures; (iii) efficient scalability up to O(10 4 ) tasks; and (iv) task-level fault tolerance. We discuss novel computational capabilities that EnTK enables and the scientific advantages arising thereof. We propose EnTK as an important addition to the suite of tools in support of production scientific computing.

Computer Science↗
DOE OSTI2021

QAOAKit: A Toolkit for Reproducible Study, Application, and Verification of the QAOA

Understanding the best known parameters, performance, and systematic behavior of the Quantum Approximate Optimization Algorithm (QAOA) remain open research questions, even as the algorithm gains popularity. We introduce QAOAKit, a Python toolkit for the QAOA built for exploratory research. QAOAKit is a unified repository of preoptimized QAOA parameters and circuit generators for common quantum simulation frameworks. We combine, standardize, and cross-validate previously known parameters for the MaxCut problem, and incorporate this into QAOAKit. We also build conversion tools to use these parameters as inputs in several quantum simulation frameworks that can be used to reproduce, compare, and extend known results from various sources in the literature. We describe QAOAKit and provide examples of how it can be used to reproduce research results and tackle open problems in quantum optimization.

Shaydulin, Ruslan↗
DOE OSTI2014

SU-E-T-519: Emission of Secondary Particles From a PMMA Phantom During Proton Irradiation: A Simulation Study with the Geant4 Monte Carlo Toolkit

Purpose: Proton therapy exhibits several advantages over photon therapy due to depth-dose distributions from proton interactions within the target material. However, uncertainties associated with protons beam range in the patient limit the advantage of proton therapy applications. To quantify beam range, positron-emitting nuclei (PEN) and prompt gamma (PG) techniques have been developed. These techniques use de-excitation photons to describe the location of the beam in the patient. To develop a detector system for implementing the PG technique for range verification applications in proton therapy, we studied the yields, energy and angular distributions of the secondary particles emitted from a PMMA phantom. Methods: Proton pencil beams of various energies incident onto a PMMA phantom with dimensions of 5 x 5 x 50 cm3 were used for simulation with the Geant4 toolkit using the standard electromagnetic packages as well as the packages based on the binary-cascade nuclear model. The emitted secondary particles are analyzed . Results: For 160 MeV incident protons, the yields of secondary neutrons and photons per 100 incident protons were ~6 and ~15 respectively. Secondary photon energy spectrum showed several energy peaks in the range between 0 and 10 MeV. The energy peaks located between 4 and 6 MeV were attributed to originate from direct proton interactions with 12C (~ 4.4 MeV) and 16O (~ 6 MeV), respectively. Most of the escaping secondary neutrons were found to have energies between 10 and 100 MeV. Isotropic emissions were found for lower energy neutrons (<10 MeV) and photons for all energies, while higher energy neutrons were emitted predominantly in the forward direction. The yields of emitted photons and neutrons increased with the increase of incident proton energies. Conclusions: A detector system is currently being developed incorporating the yields, energy and angular distributions of secondary particles from proton interactions obtained from this study.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-T-139: Meeting the Challenges of Quality Control in the TOPAS Monte Carlo Simulation Toolkit for Proton Therapy

Purpose: Monte Carlo particle transport simulation (MC) codes have become important tools in proton therapy and biology, both for research and practice. TOPAS is an MC toolkit serving users worldwide (213 licensed users at 95 institutions in 21 countries). It provides unprecedented ease in 4D placement of geometry components, beam sources and scoring through its user-friendly and reproducible parameter file interface. Quality control (QC) of stochastic simulation software is inherently difficult, and the versatility of TOPAS introduces additional challenges. But QC is vital as the TOPAS development team implements new features, addresses user feedback and reacts to upgrades of underlying software (i.e. Geant4). Methods: Whenever code is committed to our repository, over 50 separate module tests are automatically triggered via a continuous integration service. They check that the various module options execute successfully and that their results are statistically consistent with previous reference values. Prior to each software release, longer end-to-end tests automatically validate TOPAS against experimental data and a TOPAS benchmark. These include simulating multiple properties of spread-out Bragg peaks, validating nuclear models, and searching for differences in patient simulations. Results: Continuous integration has proven effective in catching regressions at the time they are introduced, particularly when implementing new features that involve refactoring code (e.g. multithreading and ntuple output). Code coverage statistics highlight untested portions of code and guide development of new tests. The various end-to-end tests demonstrate that TOPAS accurately describes the physics of proton therapy within clinical tolerances. Conclusion: The TOPAS QC strategy of frequent short tests and pre-release long tests has led to a more reliable tool. However, the versatility of TOPAS makes it difficult to predict how users might combine different modules, and so QC ultimately remains a partnership between the developer and the user. This work was funded by National Cancer Institute grant R01 CA 140735.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-G-TeP3-04: Evaluation of the Dose Enhancement with Gold Nanoparticle in Microdosimetry Level Using the Geant4-DNA Toolkit

Purpose: This study investigated the dose enhancement effect of using gold nanoparticles (GNP) as radiation sensitizers radiated by different photon beam energies. Microdosimetry of photon-irradiated GNP was determined by the Geant4-DNA process in the DNA scale. Methods: Monte Carlo simulation was conducted using the Geant4 toolkit (ver. 10.2). A GNP with different sizes (30, 50, and 100nm diameter sphere) and a DNA were placed in a water cube (1µm{sup 3}). The GNP was irradiated by photon beams with different energies (50, 100, and 150keV) and produced secondary electrons to increase the dose to the DNA. Energy depositions were calculated for both with and without GNP and to investigate the dose enhancement effect at the DNA. The distance between the GNP and DNA was varied to optimize the best GNP position to the DNA. The photon beam source was set to 200nm from the GNP in each simulation. Results: It is found that GNP had a dose enhancement effect on kV photon radiations. For Monte Carlo results on different GNP sizes, distances between the GNP and DNA, and photon beam energies, enhancement ratio was found increasing as GNP size increased. The distance between the GNP and DNA affected the result that as distance increased while the dose enhancement ratio decreased. However, the effect of changing distance was not as significant as varying the GNP size. In addition, increasing the photon beam energy also increased the dose enhancement ratio. The largest dose enhancement ratio was found to be 3.5, when the GNP (100nm diameter) irradiated by the 150keV photon beam was set to 80nm from the DNA. Conclusion: Dose enhancement was determined in the DNA with GNP in the microdosimetry scale. It is concluded that the dose enhancement varied with the photon beam energy, GNP size and distance between the GNP and DNA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Demonstration of a modeling toolkit for the design of building electrical distribution systems

The deployment of building equipment (e.g., lighting, security) and miscellaneous electrical loads that fundamentally require DC power for operation is increasing. Powering these DC loads has traditionally required an AC/DC converter, but the installation of photovoltaic (PV) and battery energy storage systems that primarily produce DC power eliminates the need for AC/DC converters at each end-device. However, analyzing system energy efficiency and cost for different electrical distribution architectures can be challenging as software tools that support this are not readily available. This paper presents preliminary results from a laboratory verification of the Building Electrical Efficiency Analysis Model (BEEAM) toolkit that was developed to address this gap. Three different eight-luminaire lighting systems comprised of market-available products were designed and modeled: one that used traditional AC distribution, a second that used a hybrid AC -to- centralized DC electrical distribution architecture, and a third that used a hybrid AC -to- distributed DC architecture. Notably, AC/DC conversions are required in all three systems. BEEAM models for LED drivers as well as Power-over-Ethernet (PoE) switches were created using laboratory characterization data. The lighting systems were simulated in Modelica, and the results were compared with each other and physics-based expectations. Simulation results show that PoE system energy efficiency is highly dependent on both device specification (e.g., LED driver and PoE switch efficiency) and system architecture (e.g., PoE switch loading) choices, as expected. For the products and system architectures selected for this study, the two DC systems were found to be less efficient than the AC system over the course of typical operation. In future work, simulation results will be compared with laboratory measurements to validate the usefulness of this software for design, and lighting systems with integrated PV and battery energy storage will be simulated to quantify the energy performance improvements that result from the elimination of some AC/DC converters.

Waghale, Anay S.↗
DOE OSTI2015

A flooding induced station blackout analysis for a pressurized water reactor using the RISMC toolkit

In this paper we evaluate the impact of a power uprate on a pressurized water reactor (PWR) for a tsunami-induced flooding test case. This analysis is performed using the RISMC toolkit: the RELAP-7 and RAVEN codes. RELAP-7 is the new generation of system analysis codes that is responsible for simulating the thermal-hydraulic dynamics of PWR and boiling water reactor systems. RAVEN has two capabilities: to act as a controller of the RELAP-7 simulation (e.g., component/system activation) and to perform statistical analyses. In our case, the simulation of the flooding is performed by using an advanced smooth particle hydrodynamics code called NEUTRINO. The obtained results allow the user to investigate and quantify the impact of timing and sequencing of events on system safety. The impact of power uprate is determined in terms of both core damage probability and safety margins.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗