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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 OSTI2022

SolarPlus-Optimizer v0.1

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this software package, we present the "Solar+ Optimizer" (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

Prakash, AnandKrishnan↗
DOE OSTI2022

TASK3 Laboratory Experiments Data

Laboratory Experiments Data of TASK3 of DOE project DE- FE0031686. Each signal has its own excel file. 150 signals are sent through the rock sample per each load configuration. There were approximately 50 to 150 load combinations tested during the experiments. Experiments were repeated after changing the polarity direction of the transducers. Signals of these repeats are in separate folders called "Reverse". There are three formations tested from the Michigan Core and four formations tested from the FutureGen site. The "Code" folder contains the Python code developed to analyze the signals. Large Dataset, please contact EDXSupport@netl.doe.gov

core↗
DOE OSTI2023

Ply Strength Prediction of Unidirectional Continuous Carbon Fiber Composites

As inhomogeneous orthotropic materials, composite mechanical properties can be difficult to predict. Even with tight fabrication process controls, there is always some microstructural variation that will affect these properties. As a highly defect-dependent phenomena, mechanical strength is even more subject to variation, especially considering that composites exhibit multiple potential failure modes. The most direct way to determine composite material strength is via experimental testing, maintaining loading and specimen morphology as close as possible to the in situ states. When multiple materials and designs are being considered, this process is often prohibitively costly and slow. However, some approximations and rules of thumb can consistently guide the design process and consideration of alternatives.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solar+ Optimizer: A Model Predictive Control Optimization Platform for Grid Responsive Building Microgrids

With the falling costs of solar arrays and battery storage and reduced reliability of the grid due to natural disasters, small-scale local generation and storage resources are beginning to proliferate. However, very few software options exist for integrated control of building loads, batteries and other distributed energy resources. The available software solutions on the market can force customers to adopt one particular ecosystem of products, thus limiting consumer choice, and are often incapable of operating independently of the grid during blackouts. In this paper, we present the “Solar+ Optimizer” (SPO), a control platform that provides demand flexibility, resiliency and reduced utility bills, built using open-source software. SPO employs Model Predictive Control (MPC) to produce real time optimal control strategies for the building loads and the distributed energy resources on site. SPO is designed to be vendor-agnostic, protocol-independent and resilient to loss of wide-area network connectivity. The software was evaluated in a real convenience store in northern California with on-site solar generation, battery storage and control of HVAC and commercial refrigeration loads. Preliminary tests showed price responsiveness of the building and cost savings of more than 10% in energy costs alone.

14 SOLAR ENERGY↗
DOE OSTI2022

Mechanisms of Mitigating Chloride-Induced Stress Corrosion Cracking of Austenitic Steels by Laser Shock Peening

This study investigates the effect of laser shock peening (LSP) on the chloride-induced stress corrosion cracking (SCC) of 304 austenitic steels. LSP can induce a high compressive residual stress to a depth of 700 µm and plastic deformation structures of dislocations, deformation twins, and stacking faults. Constant-load SCC tests in MgCl2 solution suggested that LSP can retard the crack initiation and slow the crack growth. LSP-treated subsurface layers experience ductile fracture while the central regions exhibit intergranular SCC. The LSP-induced deformation structures may impede dislocation slips, while the LSP-induced compressive residual stress can lessen the stress intensity factor of crack tips and decrease the local stress for film rupture.

Materials Science↗
NASA NTRS1964

Cumulative damage.

Cumulative fatigue damage of structural parts subjected to variable amplitude loading

LOAD TEST↗