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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 1,009 records · Page 56
All sourcesNASA NTRSDOE OSTI
NASA NTRS1966

Tooling concepts for assembly of large structures

Manufacture of the S-IC stage of the Saturn V space vehicle has resulted in new. concepts and innovations in the field of tooling. The structure size (35-ft diameter), the high reliability and accuracy requirements, and the low density or production quantity lead to a greater degree of simplicity, economy, and versatility in fabrication and assembly tooling. There are three specific concepts which should be applicable in industry, local jigging for welding, rotation of structures in vertical assemblies, and the assembly of two structures. The usual weld jigging serves a two-fold purpose: (a) to support the molten weld puddle and (b) to force and maintain alinement of the parts being welded. The extension of this method to large-diameter tanks is expensive and difficult. An alternate procedure used at MSFC is to perform free-state welding and use local jigging (stra1rclamps) and intermittent tack welding. Cylindrical structures can be accurately rotated for routing or welding on a simplified ring turntable. The tool consists of a ring of the structure diameter resting on rollers. Torque is nearly zero since the ring is rotated by friction rollers with the force being applied at the ring perimeter. Two such turntables are used at MSFC. The horizontal mating of two large components, where controlled motions of small magnitude are necessary, can be easily done by positioning units equipped with air-bearings. Such bearings are usable on concrete of minimum surface preparation and require no special air pressure source. This concept is used in assembly of the two S-IC containers.

Saturn S-IC stage↗
NASA NTRS2004

Development of a State Machine Sequencer for the Keck Interferometer: Evolution, Development and Lessons Learned using a CASE Tool Approach

This paper presents a discussion of the evolution of a sequencer from a simple EPICS (Experimental Physics and Industrial Control System) based sequencer into a complex implementation designed utilizing UML (Unified Modeling Language) methodologies and a CASE (Computer Aided Software Engineering) tool approach. The main purpose of the sequencer (called the IF Sequencer) is to provide overall control of the Keck Interferometer to enable science operations be carried out by a single operator (and/or observer). The interferometer links the two 10m telescopes of the W. M. Keck Observatory at Mauna Kea, Hawaii. The IF Sequencer is a high-level, multi-threaded, Hare1 finite state machine, software program designed to orchestrate several lower-level hardware and software hard real time subsystems that must perform their work in a specific and sequential order. The sequencing need not be done in hard real-time. Each state machine thread commands either a high-speed real-time multiple mode embedded controller via CORB A, or slower controllers via EPICS Channel Access interfaces. The overall operation of the system is simplified by the automation. The UML is discussed and our use of it to implement the sequencer is presented. The decision to use the Rhapsody product as our CASE tool is explained and reflected upon. Most importantly, a section on lessons learned is presented and the difficulty of integrating CASE tool automatically generated C++ code into a large control system consisting of multiple infrastructures is presented.

interferometer↗
NASA NTRS2007

Mission Options Scoping Tool for Mars Orbiters: Mass Cost Calculator (MC2)

Prior to developing the details of an advanced mission study, the mission architecture trade space is typically explored to assess the scope of feasible options. This paper describes the main features of an Excel-based tool, called the Mass-Cost-Calculator (MC2 ), which is used to perform rapid, high-level mass and cost options analyses of Mars orbiter missions. MC2 consists of a combination of databases, analytical solutions, and parametric relationships to enable quick evaluation of new mission concepts and comparison of multiple architecture options. The tool's outputs provide program management and planning teams with answers to "what if" queries, as well as an understanding of the driving mission elements, during the pre-project planning phase. These outputs have been validated against the outputs generated by the Advanced Projects Design Team (Team X) at NASA's Jet Propulsion Laboratory (JPL). The architecture of the tool allows for future expansion to other orbiters beyond Mars, and to non-orbiter missions, such as those involving fly-by spacecraft, probes, landers, rovers, or other mission elements.

orbiters↗
NASA NTRSDate not supplied

Lunar Browser trajectory tool

The Lunar Browser is a tool developed at NASA Ames Research Center for building, processing, and analyzing a database of lunar transfer trajectory solutions. Examples of intended uses include design trades for lunar missions and preliminary assessments of key parameters such as launch opportunities, delta-v and propulsion budgets, communication windows, eclipse durations, and lunar landing windows. The Lunar Browser tool is in the development phase and it is already producing results in its current form to address various NASA program requirements, proposals, and mission trajectories. The tool has also been used for research analysis in trajectory design, including a first publication regarding its application to the CLPS and Artemis programs. In particular, the results included transfers to lunar frozen orbits. Future work include the generation of more trajectories to expand the existing database and the optimization of the results.

Lunar Browser trajectory tool↗
DOE OSTI2014

EERE's State & Local Energy Data Tool

EERE's State and Local Energy Data (SLED) Tool provides basic energy market information that can help state and local governments plan and implement clean energy projects, including electricity generation; fuel sources and costs; applicable policies, regulations, and financial incentives; and renewable energy resource potential. Watch this video to learn more about the tool and hear testimonials from real users about the benefits of using this tool.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2016

Solar Data and Tools: Resources for Researchers, Industry, and Developers

In partnership with the U.S. Department of Energy SunShot Initiative, the National Renewable Energy Laboratory (NREL) has created a suite of analytical tools and data that can inform decisions about implementing solar and that are increasingly forming the basis of private-sector tools and services to solar consumers. The following solar energy data sets and analytical tools are available free to the public.

14 SOLAR ENERGY↗
DOE OSTI2019

A Machine-Learning Decision-Support Tool for Travel-Demand Modeling

Utility maximization(UM) models are the lifeblood of virtually all travel demand models (TDM) in practice. Be it the traditional travel demand models or more advanced activity-based models, utility maximization models are used extensively to model and predict myriad travel choices such as location choice, mode choice, route choice etc. More recently machine learning (ML) models are being applied in a variety of contexts to predict choice patterns (product suggestions on Amazon, restaurant suggestions on Yelp etc.,). In the TDM arena, there has been interest in incorporating ML models where they can enhance prediction accuracy. Though there have been sporadic efforts at comparing specific utility maximization models to machine learning models, there is a need for a standard comparison tool which can evaluate ML models against UM models for a given choice context. Addressing this need, we present a tool for applying an array of models including logit, nested logit, neural network, Naive Bayes and decision tree classifiers. The tool is specifically tailored to aid in the deciding the best model for a given choice context and can be used to choose an appropriate model family or to construct a model ensemble to improve upon current modeling standards in travel demand modeling. We test our proposed system on household vehicle count and work schedule targets from the 2017 National Household Travel Survey. Results demonstrate that for some variables, logit are not the most effective models, and the proposed system can aid in selecting a better model.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Data and Tools for Energy Planning and Analysis

The National Renewable Energy Laboratory (NREL) creates widely used data and tools to facilitate energy system planning and analysis. These software tools have been developed for complex research problems and perfected over real-world applications and laboratory validations. Some tools are award winners, others are open-source data explorers, and all are rigorously designed to empower decision-makers with accurate and accessible information. This software selection shows how NREL resources can help stakeholders achieve a clean, just, and resilient energy transformation.

data↗
DOE OSTI2023

Low-Income Energy Affordability Data (LEAD) Tool

The Low-income Energy Affordability Data (LEAD) tool was created to provide data, such as energy burden, to stakeholders to make data driven decisions. The LEAD Tool provides a starting point for local governments, NGOs, companies, etc. to find areas with higher energy burden and cost to inform decisions about funding distribution and program qualifications. This presentation was given to energy efficiency and conservation block grant program applicants to explain how this tool can help them develop their energy efficiency and conservation strategy.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Status on Development of Graphite Analytical Tool (GAT)

The DOE-ART Graphite R&D program has been generating significant amounts of irradiated and unirradiated graphite data since 2006 when the program was part of the DOE NGNP (Next Generation Nuclear Plant) Project. This data includes critical irradiation creep and irradiated material property changes from the Advanced Graphite Creep (AGR) experiment as well as significant amounts of data on unirradiated material property values on several current nuclear graphite grades (Baseline program). Previously, Idaho National Laboratory has developed an internal analysis tool to assist with analysis of the unirradiated and irradiated data. The Graphite Analytical Tool (GAT) is intended to provide easy access to the graphite data in the form of comparing unirradiated and irradiated material property changes, comparison of material property differences between various nuclear graphite grades, and illustrate trends within the irradiated and unirradiated data generated within the DOE-ART Graphite R&D program. This report summarizes the progress to-date on the development of this analytical tool.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Identifying Energy Inefficiencies in Compressed Air Systems: A Systematic Approach with the Compressed Air Scoping Tool

This paper highlights the importance of improving compressed air systems, outlines the tool’s development and features, and underscores its value as a nonbiased resource for system evaluation and optimization. Additionally, the paper presents a case study based on a food manufacturing facility to demonstrate the practical application of the tool. Furthermore, the paper discusses potential future opportunities for enhancing the CA Scoping Tool.

compressed air benchmarking↗
DOE OSTI2020

Alternative Fuels Data Center and Related Technology Integration Tools

The U.S. Department of Energy's (DOE) Office of Energy Efficiency and Renewable Energy's Vehicle Technologies Office (VTO) facilitates national coordination of the Clean Cities coalitions through its Technology Integration Program. VTO's Technology Integration Program supports a broad technology portfolio that can reduce transportation energy costs for businesses and consumers. Fleets, cities, and regions can use the tools featured in this guide to implement alternative fuels and advanced vehicles. Also learn how Clean Cities coalitions and their stakeholders across the country have used the tools.

AFDC↗
DOE OSTI2022

A graph signal processing‐based multiple model Kalman filter ( GSP‐MMKF ) tool for predictive analytics: An air separation unit process application

Abstract The industrial Air Separations Unit (ASU) is a complicated and tightly operated process. The use of dynamic process analytics is also a key element of safe and economic operation of these processes, with increasing focus on predictive analytics to take preemptive actions. With the availability of real‐time data from hundreds of sensors, the data analysis process should also consider the topology of the data, as seen in sensor networks. In this paper, a novel tool is presented that considers the complex connectivity patterns in the sensor network and uses local adaptive disturbance estimations to predict global network‐scale trends. The paper introduces the emerging field of Graph Signal Processing (GSP) and presents a rigorous derivation of the tool starting from the extraction of the sensor‐network (in a graph theoretical sense) from the data. This network, which is in the form of a matrix, is then used to derive a Kalman‐filter type of state‐space model driven by input disturbances. Multiple disturbance models (e.g., step, ramp, periodic) are included to allow the model to have different kinds of disturbance propagation. Each graph node (representing the sensors used) dynamically adapts to the most recent detected disturbance individually. These estimated disturbances are propagated to the global network using the graph. Modifications to ensure stability are also discussed. The fidelity of the tool is tested on certain downtime events and the paper concludes by discussing the advantages of the method and planned future improvements.

Ghosh, Sambit↗
DOE OSTI2017

Chapter 8: Planning Tools to Simulate and Optimize Neighborhood Energy Systems

This section introduces different energy modeling tools available in Europe and the USA for community energy master planning process varying from strategic Urban Energy Planning to more detailed Local Energy Planning. Two modeling tools used for Energy Master Planning of primarily residential communities, the 3D city model with CityGML, and the Net Zero Planner tool developed for the US Department of Defense installations are described in more details.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2017

Economic Consequence Analysis of Disasters: The ECAT Software Tool

This study develops a methodology for rapidly obtaining approximate estimates of the economic consequences from numerous natural, man-made and technological threats. This software tool is intended for use by various decision makers and analysts to obtain estimates rapidly. It is programmed in Excel and Visual Basic for Applications (VBA) to facilitate its use. This tool is called E-CAT (Economic Consequence Analysis Tool) and accounts for the cumulative direct and indirect impacts (including resilience and behavioral factors that significantly affect base estimates) on the U.S. economy. E-CAT is intended to be a major step toward advancing the current state of economic consequence analysis (ECA) and also contributing to and developing interest in further research into complex but rapid turnaround approaches. The essence of the methodology involves running numerous simulations in a computable general equilibrium (CGE) model for each threat, yielding synthetic data for the estimation of a single regression equation based on the identification of key explanatory variables (threat characteristics and background conditions). This transforms the results of a complex model, which is beyond the reach of most users, into a "reduced form" model that is readily comprehensible. Functionality has been built into E-CAT so that its users can switch various consequence categories on and off in order to create customized profiles of economic consequences of numerous risk events. E-CAT incorporates uncertainty on both the input and output side in the course of the analysis.

Environmental Economics↗
DOE OSTI2024

Deep-learning based artificial intelligence tool for melt pools and defect segmentation

Accelerating fabrication of additively manufactured components with precise microstructures is important for quality and qualification of built parts, as well as for a fundamental understanding of process improvement. Accomplishing this requires fast and robust characterization of melt pool geometries and structural defects in images. This paper proposes a pragmatic approach based on implementation of deep learning models and self-consistent workflow that enable systematic segmentation of defects and melt pools in optical images. Deep learning is based on an image-to-image translation–conditional generative adversarial neural network architecture. An artificial intelligence (AI) tool based on this deep learning model enables fast and incrementally more accurate predictions of the prevalent geometric features, including melt pool boundaries and printing-induced structural defects. We present statistical analysis of geometric features that is enabled by the AI tool, showing strong spatial correlation of defects and the melt pool boundaries. The correlations of widths and heights of melt pools with dataset processing parameters show the highest sensitivity to thermal influences resulting from laser passes in adjacent and subsequent layer passes. The presented models and tools are demonstrated on the aluminum alloy and datasets produced with different sets of processing parameters. However, they have universal quality and could easily be adapted to different material compositions. The method can be easily generalized to microstructural characterizations other than optical microscopy.

additive manufacturing↗
DOE OSTI2018

Replacement of Nitrided 33CrMoV Steel with ESR Hot Work Tool Steels for Motorsport Applications: Microstructural and Fatigue Characterization

In this work tensile strength, fatigue resistance and fracture toughness of two electroslag remelted (ESR) tool steels and of 33CrMoV12 ESR steel (both in quenched and tempered condition, as well as nitrided condition) were evaluated. The role of hardness, residual stresses and inclusion sizes on the fatigue behavior was investigated. Tool steels have a tensile strength between about 1900 and 2300 MPa, fracture toughness between 35 and 33 MPa√m, while fatigue strength ranges between 725 and 992 MPa. The tensile strength and fracture toughness of the 33CrMoV12 ESR are, respectively, 1365 MPa and about 150 MPa√m. Nitriding induces a significant increase in fatigue strength from 560 to 980 MPa. These results highlight that appropriate ESR tool steels could replace nitrided steels.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Development of Multilayer Sinter Cladding of Cold Work Tool Steel on Hadfield Steel Plates for Wear-Resistant Applications

Machinery components used for mining and mineral processing activities are often subjected to high impact loads and wear which have placed demands for the development of materials with high resistance to dynamic loads and aggressive wear conditions. In this study, a multilayered cladding of high alloyed cold work tool steel (X245VCrMo9-4), interlayered with Hadfield steel (X120Mn12) plates, which was also used as substrate using super-solidus liquid-phase sintering technique was investigated. A stack of the cold work tool steel powder was prepared with interlayered X120Mn12 steel plates in an alumina crucible at tap density with the substrate placed on it and was sintered in a vacuum furnace at 1250 °C at a heating rate of 10 K/min, held for 30 min under a nitrogen atmosphere at 0.08 MPa and furnace-cooled. Sample from the as-sintered cladding was subjected to austenization at 1000 °C, quenched in oil and tempered at 150 °C for 2 h. Samples were subjected to microstructural examination using optical and scanning electron microscopy. The microstructural investigations were supplemented by hardness and impact wear tests. Computational thermodynamics was used to support experimental findings. The results revealed that a near-net densification of the sintered X245 was achieved with 99.93 ± 0.01% density. The sintered X245 was characterized by a dispersion of vanadium carbonitride precipitates, especially at the grain boundaries. The heat-treated X245 sample had the highest hardness of 680 ± 7 HV30 due to the matrix of tempered martensitic microstructure when compared to as-sintered with hardness of 554 ± 2 HV30. The X245/X120 interface was characterized by diffusion of Cr, Mo, Mn and C, which resulted in metallurgical bonding between the cladded materials. The impact wear resistance of the sintered X245 was eight times that of the X120; hence, a tough and wear-resistant tool is anticipated when the X120 work hardened in service.

36 MATERIALS SCIENCE↗