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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 829 records · Page 46
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

Optimizing Geothermal Drilling: Oil and Gas Technology Transfer

There is a significant amount of financial risk associated with geothermal drilling. This study of drilling operations seeks opportunities to improve upon current practices and technologies. The scope of this study included analyzing 21 geothermal wells and 21 oil and gas wells. The goal was to determine a 'Perfect Well' using historical data to compare the best oil and gas well to the best geothermal well. Unfortunately, limitations encountered in the study included missing data (bit records, mud information, etc.) and poor data collection practices An online software database was used to format drilling data to IADC coded daily drilling reports and generate figures for analysis. Six major issues have been found in geothermal drilling operations. These problems include lost circulation, rig/ equipment selection, cementing, penetration rate, drilling program, and time management. As a result of these issues, geothermal drilling averaged 56.4 days longer than drilling comparable oil and gas wells in the wells in this study. Roughly $13.9 million was spent on non-productive time in the 21 geothermal wells, compared with only $1.3 million in the oil and gas wells, assuming a cost of $50,000 per day. Comparable events such as drilling the same sized hole, tripping in/out, cementing, and running the same size casing took substantially less time in the oil and gas wells. Geothermal wells were drilled using older and/or less advanced technology to depths less than 10,000 feet, while oil and gas wells reached 12,500 feet faster with purpose built rigs. A new approach is now underway that will optimize drilling programs throughout the drilling industry using Mechanical Specific Energy (MSE) as a tool to realize efficient drilling processes. Potential improvements for current geothermal operations are: the use of electronic records, real time services, and official glossary terms to describe rig operations, and advanced drilling rigs/technology.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Optimizing Geothermal Drilling: Oil and Gas Technology Transfer

There is a significant amount of financial risk associated with geothermal drilling; however, there are opportunities to improve upon current practices and technologies used. The scope of this drilling operational study included 21 geothermal wells and 21 oil and gas wells. The goal was to determine a 'perfect well' using historical data to compare the best oil and gas well to the best geothermal well. Unfortunately, limitations encountered in the study included missing data (bit records, mud information, etc.), poor data collection, and difficult to ascertain handwriting. An online software database was used to format drilling data to IADC coded daily drilling reports and generate analysis figures. Six major issues have been found in geothermal drilling operations. These problems include lost circulation, rig/equipment selection, cementing, penetration rate, drilling program, and time management. As a result of these issues, geothermal drilling averages 56.4 days longer than drilling comparable oil and gas wells in the wells in this study. Roughly $13.9 million would be lost due to non-productive time in the 21 geothermal wells and only $1.3 million in the oil and gas wells, assuming a cost of $50,000 per day. Comparable events such as drilling the same sized hole, tripping in/out, cementing, and running the same size casing took substantially less time in the oil and gas wells. Geothermal wells were drilled using older and/or less advanced technology to depths less than 10,000 feet, while oil and gas wells reached 12,500 feet faster with purpose built rigs. A new approach is now underway that will optimize drilling programs throughout the drilling industry. It is the use of Mechanical Specific Energy (MSE) as a tool to realize efficient drilling processes. However, a work-flow must also be established in order for there to be an efficient drilling program. Potential improvements for current geothermal operations are: the use of electronic records, real time services, and official glossary terms to describe rig operations, and advanced drilling rigs/technology.

15 GEOTHERMAL ENERGY↗
DOE OSTI2017

Evaluating the networking characteristics of the Cray XC-40 Intel Knights Landing-based Cori supercomputer at NERSC

There are many potential issues associated with deploying the Intel Xeon Phi™ (code named Knights Landing [KNL]) manycore processor in a large-scale supercomputer. One in particular is the ability to fully utilize the high-speed communications network, given that the serial performance of a Xeon Phi TM core is a fraction of a Xeon®core. In this paper, we take a look at the trade-offs associated with allocating enough cores to fully utilize the Aries high-speed network versus cores dedicated to computation, e.g., the trade-off between MPI and OpenMP. In addition, we evaluate new features of Cray MPI in support of KNL, such as internode optimizations. We also evaluate one-sided programming models such as Unified Parallel C. We quantify the impact of the above trade-offs and features using a suite of National Energy Research Scientific Computing Center applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Optimizing I/O Forwarding Techniques for Extreme-Scale Event Tracing

Programming development tools are a vital com- ponent for understanding the behavior of parallel applica- tions. Event tracing is a principal ingredient to these tools, but new and serious challenges place event tracing at risk on extreme-scale machines. As the quantity of captured events increases with concurrency, the additional data can over- load the parallel file system and perturb the application be- ing observed. In this work we present a solution for event tracing on extreme-scale machines. We enhance an I/O for- warding software layer to aggregate and reorganize log data prior to writing to the storage system, significantly reduc- ing the burden on the underlying file system. Furthermore, we introduce a sophisticated write buffering capability to limit the impact. To validate the approach, we employ the Vampir tracing toolset using these new capabilities. Our re- sults demonstrate that the approach increases the maximum traced application size by a factor of 5x to more than 200,000 processes.

atomic append↗
DOE OSTI2023

QMMM 2023: A program for combined quantum mechanical and molecular mechanical modeling and simulations

Combined quantum mechanical and molecular mechanical (QM/MM) methods play an important role in multiscale modeling and simulations. QMMM 2023 is a general-purpose program for single-point calculations, geometry optimizations, transition-state optimizations, and molecular dynamics (MD) at the QM/MM level. It calls a QM package and an MM package to perform the required single-level calculations and combines them into a QM/MM energy by a variety of schemes. QMMM 2023 supports GAMESS-US, Gaussian, and ORCA as QM packages and Tinker as the MM package. Four types of treatments are available for embedding the QM subsystem in the MM environment: mechanical embedding with gas-phase calculations of the QM region, electronic embedding that allows polarization of the QM region by the MM environment, polarizable embedding for mutual polarization of the QM and MM regions, and flexible embedding for both mutual polarization and partial charge transfer between the QM and MM regions. Boundaries between QM and MM regions that pass through covalent bonds can be treated by several methods, including the redistributed charge (RC) scheme, redistributed charge and dipole (RCD) scheme, balanced-RC scheme, balanced-RCD scheme, screened charge scheme that takes account of charge penetration effects, and smeared charge scheme that delocalizes the MM charges near the QM–MM boundary. Geometry optimization can be done using the optimizer implemented in QMMM 2023 or the Berny optimizer in Gaussian through external calls to Gaussian. Molecular dynamics simulations can be performed at the pure-MM level, pure-QM level, fixed-partitioning QM/MM level, and adaptive-partitioning QM/MM level. As a result, the adaptive-partitioning treatments permit on-the-fly relocation of the QM–MM boundary by dynamically reclassifying atoms or groups into the QM or MM subsystems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2014

Layer-by-layer charging in non-volatile memory devices using embedded sub-2 nm platinum nanoparticles

In this work, we demonstrate multi-level operation of a non-volatile memory metal oxide semiconductor capacitor by controlled layer-by-layer charging of platinum nanoparticle (PtNP) floating gate devices with defined gate voltage bias ranges. The device consists of two layers of ultra-fine, sub-2 nm PtNPs integrated between Al{sub 2}O{sub 3} tunneling and separation layers. PtNP size and interparticle distance were varied to control the particle self-capacitance and associated Coulomb charging energy. Likewise, the tunneling layer thicknesses were also varied to control electron tunneling to the first and second PtNP layers. The final device configuration with optimal charging behavior and multi-level programming was attained with a 3 nm Al{sub 2}O{sub 3} initial tunneling layer, initial PtNP layer with particle size 0.54 ± 0.12 nm and interparticle distance 4.65 ± 2.09 nm, 3 nm Al{sub 2}O{sub 3} layer to separate the PtNP layers, and second particle layer with 1.11 ± 0.28 nm PtNP size and interparticle distance 2.75 ± 1.05 nm. In this device, the memory window of the first PtNP layer saturated over a programming bias range of 7 V to 14 V, after which the second PtNP layer starts charging, exhibiting a multi-step memory window with layer-by-layer charging.

36 MATERIALS SCIENCE↗
DOE OSTI2020

PyMDA : microcrystal data assembly using Python

The recent developments at microdiffraction X-ray beamlines are making microcrystals of macromolecules appealing subjects for routine structural analysis. Microcrystal diffraction data collected at synchrotron microdiffraction beamlines may be radiation damaged with incomplete data per microcrystal and with unit-cell variations. A multi-stage data assembly method has previously been designed for microcrystal synchrotron crystallography. Here the strategy has been implemented as a Python program for microcrystal data assembly ( PyMDA ). PyMDA optimizes microcrystal data quality including weak anomalous signals through iterative crystal and frame rejections. Beyond microcrystals, PyMDA may be applicable for assembling data sets from larger crystals for improved data quality.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Sequential Perturbation-based FDIA Detection using DERs for Unbalanced Distribution System

The power distribution system with its reliance on automated monitoring and control infrastructure makes it a complicated cyber-physical system and vulnerable to various cyber-attacks. This paper proposes a moving target defense inspired false data injection attack (FDIA) detection mechanism for an unbalanced distribution system. In the proposed grid diagnosis service framework, the distribution system operator judiciously manipulates power outputs of a subset of inverter-based distribution energy resources (DERs) to create secret low magnitude voltage perturbations which are inconsequential to the normal operation of the grid. A mixed-integer-linear-programming algorithm is developed to select the optimal set of DERs that can create a voltage perturbation signal of the required magnitude at each sensor location at a minimum cost. Then, a sequential detector is applied that detects for the FDIA as measurements are received from individual sensors. The performance of the proposed perturbation-based FDIA detection framework is demonstrated via simulation of the IEEE 123 bus test system.

Attack Detection↗
DOE OSTI2019

Community Microgrid Planning Considering Building Thermal Dynamics

In this paper, the building thermal dynamic characteristics are introduced in the community microgrid (MG) planning model. The proposed planning model is formulated as a mixed integer linear programming (MILP) which seeks to determine the optimal deployment strategy for various distributed energy resources (DER). The objective is to minimize the annualized cost of community MG, including investment cost in DER, operation cost for dispatchable fuel-generators (DFG), energy storage system (ESS) degradation cost, energy purchasing and peak demand charge at PCC, customer discomfort cost due to the room temperature deviation and load curtailment cost. Given the slow thermal dynamic characteristics of buildings, the heating, ventilation and air-conditioning (HVAC) system in the proposed model is treated as a demand side management (DSM) component, whose dispatch commands are provided by the central MG controller. Numerical results based on a community MG comprising of 20 residential buildings demonstrate the effectiveness of the proposed planning model and the benefits of introducing the building thermal dynamic model.

Zhang, Xiaohu↗
DOE OSTI2019

Generalized Graph Laplacian Based Anomaly Detection for Spatiotemporal MicroPMU Data

This letter develops a novel anomaly detection method using the generalized graph Laplacian (GGL) matrix to visualize the spatiotemporal relationship of distribution-level phasor measurement unit (uPMU) data. The uPMU data in a specific time horizon is segregated into multiple segments. An optimization problem formulated as a Lagrangian function is utilized to estimate the GGL matrix. During the iterative process, an optimal update is constituted as a quadratic program (QP) problem. To perform the uPMU-based spatiotemporal analysis, normalized diagonal elements of GGL matrix are proposed as a quantitative metric. The effectiveness of the developed method is demonstrated through real-world uPMU measurements gathered from test feeders in Riverside, CA.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

End-to-End Workflow for Machine-Learning-Based Qubit Readout With QICK and hls4ml

In this article, we present an end-to-end workflow for superconducting qubit readout that embeds codesigned neural networks into the quantum instrumentation control kit (QICK). Capitalizing on the custom firmware and software of the QICK platform, which is built on Xilinx radiofrequency system-on-chip field-programmable gate arrays (FPGAs), we aim to leverage machine learning (ML) to address critical challenges in qubit readout accuracy and scalability. The workflow utilizes the hls4ml package and employs quantization-aware training to translate ML models into hardware-efficient FPGA implementations via user-friendly Python application programming interfaces. We experimentally demonstrate the design, optimization, and integration of an ML algorithm for single transmon qubit readout, achieving 96% single-shot fidelity with a latency of 32.25 ns and less than 16% FPGA lookup table resource utilization. Our results offer the community an accessible workflow to advance ML-driven readout and adaptive control in quantum information processing applications.

42 ENGINEERING↗
DOE OSTI2014

SU-F-19A-08: Optimal Time Release Schedule of In-Situ Drug Release During Permanent Prostate Brachytherapy

Purpose: Permanent prostate brachytherapy spacers can be used to deliver sustained doses of radiosentitizing drug directly to the target, in order to enhance the radiation effect. Implantable nanoplatforms for chemo-radiation therapy (INCeRTs) have a maximum drug capacity and can be engineered to control the drug release schedule. The optimal schedule for sensitization during continuous low dose rate irradiation is unknown. This work studies the optimal release schedule of drug for both traditional sensitizers, and those that work by suppressing DNA repair processes. Methods: Six brachytherapy treatment plans were used to model the anatomy, implant geometry and calculate the spatial distribution of radiation dose and drug concentrations for a range of drug diffusion parameters. Three state partial differential equations (cells healthy, damaged or dead) modeled the effect of continuous radiation (radiosensitivities α,β) and cellular repair (time tr) on a cell population. Radiosensitization was modeled as concentration dependent change in α,β or tr which with variable duration under the constraint of fixed total drug release. Average cell kill was used to measure effectiveness. Sensitization by means of both enhanced damage and reduced repair were studied. Results: Optimal release duration is dependent on the concentration of radiosensitizer compared to the saturation concentration (csat) above which additional sensitization does not occur. Long duration drug release when enhancing α or β maximizes cell death when drug concentrations are generally over csat. Short term release is optimal for concentrations below saturation. Sensitization by suppressing repair has a similar though less distinct trend that is more affected by the radiation dose distribution. Conclusion: Models of sustained local radiosensitization show potential to increase the effectiveness of radiation in permanent prostate brachytherapy. INCeRTs with high drug capacity produce the greatest benefit with drug release over weeks. If in-vivo drug concentrations are not able to approach saturation concentration, durations of days is optimal. DOD 1R21CA16977501; A. David Mazzone Awards Program 2012PD164.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

A Reference Implementation for a Quantum Message Passing Interface

Practical applications of quantum computing are currently limited by the number of qubits that can be set with reasonable fidelities for each system. Therefore, a distributed quantum computing system with multiple quantum computers coherently connected is highly demanding. To realize the internode communication of quantum information, the software interface, Quantum Message Passing Interface (QMPI), leveraging the framework built for classical MPI but taking advantage of quantum teleportation to communicate between different quantum nodes was proposed. In this project, we develop the QMPI with point-to-point and collective operations in Qiskit and characterize its performance by demonstrating the application implementations. Moreover, we developed a new technique for optimizing collective communication of the distributed quantum programs with Multi-Controlled Toffoli gates. This technique beats the state-of-the-art in terms of fidelity and the number of remote EPR pairs consumed in both simulations and experiments.

Shi, Yue↗
DOE OSTI2015

Slope Extensions to ASL Library

Extensions to the AMPL/solver interface library (http://netlib.sandia.gov/ampl/solvers) to compute bounds on algebraic expressions, plus a test program. use in uncertainty quantification and global optimization algorithms. This software is not primarily for military applications.

Gay, David↗
DOE OSTI2023

Justice 40 Tool (J40 Tool) v1.0

The Justice 40 tool provides a quantitative framework to support decision-making around equitable energy interventions at the community level. The tool calculates the optimal portfolio of policy interventions that explicitly mitigates energy insecurity of an eligible population, by reducing its disproportionate energy burden. The place-based analysis assumes a spatial census tract-level resolution and distinguishes different sociodemographic groups within each tract. Instead of focusing on a specific technology, the underlying J40 model captures the combined effect of a set of policy interventions, currently including weatherization, rooftop solar, community solar and community wind. For each tract, the model chooses the optimal (least cost) combination of interventions to address the disproportionate burden, considering the specific population demographics and techno-economic potentials of technologies. Mathematically, this problem is formalized as an optimization model and formulated as a linear program.

Heleno, Miguel↗
DOE OSTI2018

Best Practices for Operation and Maintenance of Photovoltaic and Energy Storage Systems; 3rd Edition

The goal of this guide is to reduce the cost and improve the effectiveness of operations and maintenance (O&M) for photovoltaic (PV) systems and combined PV and energy storage systems. Reported O&M costs vary widely based on the requirements of the system and the nature of the O&M contract, but a more standardized approach to planning and delivering O&M has the potential to both decrease costs and make those costs more predictable over time. This guide encourages adoption of best practices to reduce the cost of O&M and improve the performance of fielded systems, but it also enhances financing of new projects by making cost more predictable and mitigating performance risk. This guide also includes technical improvement opportunities in the design of systems and in specification of equipment because high-quality system deployment improves lifetime project performance and energy production while reducing, or at least optimizing, costs to deliver an O&M program. This guide provides recommendations that increase the effectiveness of O&M services; reduce O&M costs, improve solar asset transparency for investors and rating agencies; provide an industry framework for quality management; and reduce transaction costs.

14 SOLAR ENERGY↗
DOE OSTI2024

Complete Demonstration of a Prototype Version of FORCE User Interface and Conduct Analyst Survey Collecting Feedback on Interface Features and Usability

In 2024 the US Department of Energy (DOE) Office of Nuclear Energy (NE) Integrated Energy System (IES) program continued to develop the Framework for Optimization of Resources and Economics (FORCE) analysis ecosystem into a more traditional toolset with simplified software installation, automated workflows, and interactive results visualization. The DOE-NE Nuclear Energy Advanced Modeling and Simulation (NEAMS) Workbench continued to be leveraged for user input, application workflow and runtime environment, and interactive results visualization capabilities. This report documents the demonstration of a FORCE User Interface (UI) prototype and the results of a survey of analysts’ using the Holistic Energy Resource Optimization Network (HERON) tool in FORCE with the prototype UI.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE↗