SEARCH · Search NASA

Results for “modular process”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

NASA NTRS1992

Monthly mean global satellite data sets available in CCM history tape format

Satellite data for climate monitoring have become increasingly important over the past decade, especially with increasing concern for inadvertent antropogenic climate change. Although most satellite based data are of short record, satellites can provide the global coverage that traditional meteorological observations network lack. In addition, satellite data are invaluable for the validation of climate models, and they are useful for many diagnostic studies. Herein, several satellite data sets were processed and transposed into 'history tape' format for use with the Community Climate Model (CCM) modular processor. Only a few of the most widely used and best documented data sets were selected at this point, although future work will expand the number of data sets examined as well as update the archived data sets. An attempt was made to include data of longer record and only monthly averaged data were processed. For studies using satellite data over an extended period, it is important to recognize the impact of changes in instrumentation, drift in instrument calibration, errors introduced by retrieval algorithms and other sources of errors such as those resulting from insufficient space and/or time sampling.

Hurrell, James W.↗

DOE OSTI2021

Towards developing multiscale-multiphysics models and their surrogates for digital twins of metal additive manufacturing

Artificial intelligence (AI) embedded within digital models of manufacturing processes can be used to improve process productivity and product quality significantly. The application of such advanced capabilities particularly to highly digitalized processes such as metal additive manufacturing (AM) is likely to make those processes commercially more attractive. AI capabilities will reside within Digital Twins (DTs) which are living virtual replicas of the physical processes. DTs will be empowered to operate autonomously in a diagnostic control capacity to supervise processes and can be interrogated by the practitioner to inform the optimal processing route for any given product. The utility of the information gained from the DTs would depend on the quality of the digital models and, more importantly, their faster-solving surrogates which dwell within DTs for consultation during rapid decision-making. In this article, we point out the exceptional value of DTs in AM and focus on the need to create high-fidelity multiscale-multiphysics models for AM processes to feed the AI capabilities. We identify technical hurdles for their development, including those arising from the multiscale and multiphysics characteristics of the models, the difficulties in linking models of the subprocesses across scales and physics, and the scarcity of experimental data. We discuss the need for creating surrogate models using machine learning approaches for real-time problem-solving. We further identify non-technical barriers, such as the need for standardization and difficulties in collaborating across different types of institutions. We offer potential solutions for all these challenges, after reflecting on and researching discussions held at an international symposium on the subject in 2019. Here, we argue that a collaborative approach can not only help accelerate their development compared with disparate efforts, but also enhance the quality of the models by allowing modular development and linkages that account for interactions between the various sub-processes in AM. A high-level roadmap is suggested for starting such a collaboration.

36 MATERIALS SCIENCE↗

DOE OSTI2020

Flexible and Modular Simultaneous Modeling of Flow and Reactive Transport in Rivers and Hyporheic Zones

Investigations of coupled multiphysics processes in rivers and hyporheic zones have extensively used numerical models. Most existing models use a sequential, one-way coupling between the surface and subsurface domains. Such one-way coupling potentially introduces error. To overcome this, a fully coupled model, hyporheicFoam, was developed using the open-source computational platform OpenFOAM. It captures the coupled flow and multicomponent reactive transport processes within both surface and subsurface domains and across their interface. The coupling between two domains is implemented by mapping conservative flux boundary conditions at the interface through an iterative algorithm. Reactive transport is enabled by specifying a reaction network. To start, we have implemented reaction kinetics following the double Monod-type model with inhibition. The model capability is illustrated through modeling of both conservative and reactive hyporheic flow and transport through dune bedforms. With the novel coupled model, it is now possible to quantify reactions wherein the reactants and products are constantly exchanging between domains and have feedbacks. hyporheicFoam can simulate large, three-dimensional cases owing to the computational flexibility and power offered by the code structure and parallel design of OpenFOAM.

58 GEOSCIENCES↗

NASA NTRS2022

Validation of the Mars 2020 Fault Protection Design: Navigating the Infinity of the Off-Nominal

On July 30th 2020, the Mars 2020 mission successfully launched out of Cape Canaveral, Florida, passed through the Earth’s shadow, and began its short cruise to Mars. Less than seven months later, the Perseverance rover touched down safely in Jezero Crater to begin its ambitious mission that includes looking for signs of ancient life and collecting samples for future return to Earth. Getting to the successful landing, or “Tango Delta Nominal,” could not have been achieved without also considering the off-nominal. One of the teams supporting this ambitious mission is the fault protection (FP) team. This team is tasked with assessing the various failures, or faults, that could prevent mission success and with ensuring that the autonomous behaviors built into the software and hardware can detect faults and recover the vehicle to a safe state. As part of its charter, the FP team designed a test campaign to provide confidence in the system’s robustness to off-nominal scenarios across all of Mars 2020’s mission phases. The greatest challenge associated with designing such a validation campaign was reducing the infinite number of anomalous scenarios into a finite test suite. In addition, the tests needed to be executed efficiently in order to utilize the team’s limited test venue access, but still needed to maintain a level of rigor that guaranteed confidence in the test outcomes. Given that each test scenario generated massive amounts of data, the team also developed methods for quickly ascertaining whether the autonomous fault protection behaviors maintained vehicle safety in the presence of an anomaly. This paper summarizes the processes that the Mars 2020 fault protection team employed to execute its off-nominal validation campaign. It captures both the methods of generating a suite of off-nominal tests, as well as reducing it to a subset that can be realistically executed within schedule and resource constraints. It also describes the various processes and philosophies that the team utilized to execute the tests efficiently, including creating a standardized procedure template, keeping the test cases modular so that they could be easily interchanged, and capturing common fault injections in a change-controlled database. Finally, it will describe the tools and processes for assessing the test data, focusing in particular on a tool that evaluated vehicle state using “secondary” sources of data to validate that the software had truly configured the spacecraft to the expected safe state.

Morantz, Chaz↗

DOE OSTI2021

Modular supply chain optimization considering demand uncertainty to manage risk

Supply chain under demand uncertainty has been a challenging problem due to increased competition and market volatility in modern markets. Flexibility in planning decisions makes modular manufacturing a promising way to address this problem. We report the problem of multiperiod process and supply chain network design is considered under demand uncertainty. A mixed integer two-stage stochastic programming problem is formulated with integer variables indicating the process design and continuous variables to represent the material flow in the supply chain. The problem is solved using a rolling horizon approach. Benders decomposition is used to reduce the computational complexity of the optimization problem. To promote risk-averse decisions, a downside risk measure is incorporated in the model. The results demonstrate the several advantages of modular designs in meeting product demands. A pareto-optimal curve for minimizing the objectives of expected cost and downside risk is obtained.

42 ENGINEERING↗

NASA NTRS1975

Low-cost data analysis systems for processing multispectral scanner data

A research-oriented data analysis system was developed which is used for evaluating complex remote sensor systems and for development of techniques for application of remotely sensed data. Some modular hardware components were developed which may be added to one's existing facilities to establish a low-cost data analysis system for processing multispectral scanner data. Software modules which are compatible with small general purpose digital computers process and analyze remote sensor data, and convert it to information needed by users. The software modules are written in FORTRAN IV language for ease of transfer to other computer systems. The basic hardware and software system requirements are defined for some low-cost data analysis systems consisting of an image display system, a small general purpose digital computer, and an output recording device. The hardware modules consist of: a LANDSAT MSS data reformatting program; a series of spectral pattern recognition programs required to generate surface classification maps and tabular information; programs to convert computer generated maps from image space to a geographically referenced base; programs to extract data and irregularly shaped areas and to produce thematic maps of the designated areas; and programs to tabulate acreages of selected classification categories. Some off-the-shelf, inexpensive digital image display systems are described.

Whitley, S. L.↗

NASA NTRS2020

Dynamic IT Security Database and Analytics for Launch Control Systems Software

During the Summer 2020 session, I worked with intern Destani S. Van Arsdalen of EGS Software. Together, we co-created a tool to aid the dynamic investigation, updated over time,of the security compliance of LCS COTS and open source software. We originally planned touse spreadsheet software for management and analysis, but through this exploratoryproject, chose to use Python and JSON after receiving feedback on our project’s current anddesired capabilities at that time.At first, the project was solely designed to help on-board new COTS software, based on aquestionnaire that could be filled out for each software package. This, combined with usingthe spreadsheet application’s web-query capabilities to fetch information from the NVD,allowed presentation and analytics cells to automatically populate as elements of themanually-filled questionnaire changed. While this system was promising, we decided tochange technologies for a few reasons. In the spreadsheet, single cells could not hold complexdata like arrays and objects. The automatic population of cells and dynamic updates made itdifficult to manage and add new features. And finally, it had limited extensibility sinceadding new software required significant understanding of how both the spreadsheet wasconstructed, and the more obscure, proprietary scripting languages packaged with it.The pivot to a standard computer science database language of JSON, aided by thescripting capabilities of Python, greatly helped to improve the project’s functionality. First,and most importantly, the script’s import and analysis of database data is easilyreproducible. Additional data analysis can be modularly added without requiringmodification of the script and is capable of routine scheduling. The revised process can besplit into three parts. First, the conversion of LCS asset and software documentation into theJSON hierarchical database format. Second, the merging of this database with the NVD,forming a new data structure, using CPEs of the CVE object as a linking element betweenthem. And third, the automatically performed analytics and analysis of the combined data,in a modular and extensible format, to produce better informed business decisions. The outputted graphs, for example, are automatically generated by the Python script inconnection with the combined database. This allows updated graphs and any analytics to be re-rendered automatically following updates to the LCS’s initial asset documentation. Afinal report can then be programmatically and easily constructed from these sources to allow fully reproducible metrics for heavily evidenced risk management decisions.

it↗

DOE OSTI2021

Water desalination through the dewpoint evaporative system

This paper presents the first numerical analysis of a novel Dew Point Desalination unit (DPD), which utilizes the phenomenon of the evaporative cooling process to minimize energy consumption. The proposed solution is based on a modular structure, which allows it to obtain any required water production capacity. The analyses for various operational parameters and various climatic conditions are based on the numerical simulations conducted using a validated mathematical model. The system performance was described with different factors, including specific energy consumption (SEC) and daily water production rate respected to 1 m^3*s^-1 of passing air stream (DWP). It is shown that the DPD system can operate in almost every climate zone, and the desalinated water production consumes less than 1.5 kWh*m^-3 of electric energy It is noted the best performance of the DPD system is achieved in the semi-arid, desert and subtropical climate zones. In these climate zones, the 2-stage DPD system allows the production of desalinated water with an electric energy consumption SEC lower than 0.5 kWh*m^-3. The additional benefit of the DPD system is its modularity. The presented DPD system stands as a module, that can be multiplied as needed to achieve the desired size of the desalination plant.

Desalination↗

DOE OSTI2020

Desalination for a circular water economy

Today's water systems are enabled by ample fresh water sources, low-cost centralized treatment, and facile wastewater disposal. Climatic change, aging infrastructure, and source water contamination have exposed the vulnerabilities of this linear water paradigm. While seawater desalination enables coastal communities to augment their supply, more broadly securing water systems for municipal, industrial, and agricultural water users will require distributed desalination and fit-for-purpose reuse of nontraditional water sources. Our linear water economy must evolve into a resilient circular water economy, where water is continuously reused and “contaminants” become the feedstocks for other economically valuable processes. Additionally, technology innovation is needed to deliver autonomous, precise, resilient, intensified, modular, and electrified desalination systems that reduce the cost, improve the performance, and enhance the resilience of nontraditional water reuse systems. Meanwhile, strong federal leadership and coordination is needed to accelerate desalination research, promote information gathering efforts to direct technology development, and create an expanded role for non-profit organizations in knowledge dissemination.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2019

Parallel-in-Time Simulation Algorithm for Power Electronics: MMC-HVdc System

The complexity in simulating power electronics like modular multilevel converters (MMCs) requires simulation algorithms to speed-up the process. Existing simulation algorithms exploit spatial parallelism to speed-up simulation. With rise in complexity of power electronics and presence of increased number of states within them, there are limits in the speed-up using spatial parallelism. In this paper, a temporal parallelism algorithm based on parallel-in-time methods is developed for simulation of power-electronics-systems. The temporal parallelism algorithm is based on computation of power-electronics-states on coarse and fine time-steps using different models. The models of power-electronics-systems used in coarse and fine time-steps are average-value and detailed models, respectively. The updates to states on coarse time-step are computed serially and are used to initialize the states on fine time-step. The updates on fine time-step are computed in parallel. A translation method is proposed in this paper to update the states on fine time-step from the simulations in the coarse time-step, and vice-versa. The proposed algorithm is applied to simulate MMCs and is validated with respect to a detailed reference MMC model. The proposed algorithm recorded a speed-up of up to 3.47× with 5 cores.

42 ENGINEERING↗

DOE OSTI2023

Sandia Contributions to WaterTAP

SAND2023-06591O Through National Alliance for Water Innovation funding, Sandia will be contributing to the Water treatment Technoeconomic Assessment Platform (WaterTAP) project. WaterTAP is an open-source, Python-based software package that supports the technoeconomic assessment of full water treatment trains. WaterTAP includes a modular water treatment model library spanning a broad set of water treatment processes composed of unit, property, and costing models.

Rawlings, EdnaSoraya↗

DOE OSTI2024

Insights into the action of phylogenetically diverse microbial expansins on the structure of cellulose microfibrils

Microbial expansins (EXLXs) are non-lytic proteins homologous to plant expansins involved in plant cell wall formation. Due to their non-lytic cell wall loosening properties and potential to disaggregate cellulosic structures, there is considerable interest in exploring the ability of microbial expansins (EXLX) to assist the processing of cellulosic biomass for broader biotechnological applications. Herein, EXLXs with different modular structure and from diverse phylogenetic origin were compared in terms of ability to bind cellulosic, xylosic, and chitinous substrates, to structurally modify cellulosic fibrils, and to boost enzymatic deconstruction of hardwood pulp. Five heterogeneously produced EXLXs (Clavibacter michiganensis; CmiEXLX2, Dickeya aquatica; DaqEXLX1, Xanthomonas sacchari; XsaEXLX1, Nothophytophthora sp.; NspEXLX1 and Phytophthora cactorum; PcaEXLX1) were shown to bind xylan and hardwood pulp at pH 5.5 and CmiEXLX2 (harboring a family-2 carbohydrate-binding module) also bound well to crystalline cellulose. Small-angle X-ray scattering revealed a 20–25% increase in interfibrillar distance between neighboring cellulose microfibrils following treatment with CmiEXLX2, DaqEXLX1, or NspEXLX1. Correspondingly, combining xylanase with CmiEXLX2 and DaqEXLX1 increased product yield from hardwood pulp by ~ 25%, while supplementing the TrAA9A LPMO from Trichoderma reesei with CmiEXLX2, DaqEXLX1, and NspEXLX1 increased total product yield by over 35%. This direct comparison of diverse EXLXs revealed consistent impacts on interfibrillar spacing of cellulose microfibers and performance of carbohydrate-active enzymes predicted to act on fiber surfaces. These findings uncover new possibilities to employ EXLXs in the creation of value-added materials from cellulosic biomass.

09 BIOMASS FUELS↗

DOE OSTI2021

Granick revisited: Synthesizing evolutionary and ecological evidence for the late origin of bacteriochlorophyll via ghost lineages and horizontal gene transfer

Photosynthesis—both oxygenic and more ancient anoxygenic forms—has fueled the bulk of primary productivity on Earth since it first evolved more than 3.4 billion years ago. However, the early evolutionary history of photosynthesis has been challenging to interpret due to the sparse, scattered distribution of metabolic pathways associated with photosynthesis, long timescales of evolution, and poor sampling of the true environmental diversity of photosynthetic bacteria. Here, we reconsider longstanding hypotheses for the evolutionary history of phototrophy by leveraging recent advances in metagenomic sequencing and phylogenetics to analyze relationships among phototrophic organisms and components of their photosynthesis pathways, including reaction centers and individual proteins and complexes involved in the multi-step synthesis of (bacterio)-chlorophyll pigments. We demonstrate that components of the photosynthetic apparatus have undergone extensive, independent histories of horizontal gene transfer. This suggests an evolutionary mode by which modular components of phototrophy are exchanged between diverse taxa in a piecemeal process that has led to biochemical innovation. We hypothesize that the evolution of extant anoxygenic photosynthetic bacteria has been spurred by ecological competition and restricted niches following the evolution of oxygenic Cyanobacteria and the accumulation of O 2 in the atmosphere, leading to the relatively late evolution of bacteriochlorophyll pigments and the radiation of diverse crown group anoxygenic phototrophs. This hypothesis expands on the classic “Granick hypothesis” for the stepwise evolution of biochemical pathways, synthesizing recent expansion in our understanding of the diversity of phototrophic organisms as well as their evolving ecological context through Earth history.

58 GEOSCIENCES↗

DOE OSTI2026

Topological Control of Triply Periodic Minimal Surfaces for Thermal Design and Advanced Manufacturing: A Gyroid Case Study

Recently, there has been a heightened interest in using triply periodic minimal surfaces (TPMSs) in the design of compact process engineering components. The benefits of high surface area per unit volume, modular form, and inherent periodicity provide a holistic self-supporting network and flow-conducive features. Applications of importance include thermal power management, biomimetic scaffolds and structures, and feasibility of advanced manufacturing. This study presents a novel approach to the manipulation of the characteristic Schwarz-G, or gyroid TPMS, for thermal design in the context of advanced manufacturing. The study presents relationships between design parameters and resulting surface area as a target response using the characteristic equation of a gyroid. Through parametric control, the characteristic equation is manipulated to produce a 20-fold increase in achievable area over a baseline design characteristic of 25.4 mm through controlled combinations of design parameters. A second relationship is presented as a function of the maximum area achieved and manipulated design parameters. Through the analysis, the study presents a framework to identify and maximize the achievable area of TPMSs for advanced manufacturing and thermal management applications.

gyroid↗

NASA NTRS1968

Laminated sheet composites reinforced with modular filament sheet

Aluminum and magnesium composite sheet laminates reinforced with low density, high strength modular filament sheets are produced by diffusion bonding and explosive bonding. Both processes are accomplished in normal atmosphere and require no special tooling or cleaning other than wire brushing the metal surfaces just prior to laminating.

Reece, O. Y.↗

NASA NTRS1977

Instrumentation and data acquisition systems

A comprehensive and integrated measurement system was identified and a design and development effort initiated to meet the criteria imposed by the National Transonic Facility operating environment. Specific measurement areas receiving concentrated attention include: data acquisition, force measurement, pressure instrumentation, flow visualization techniques, model attitude and model deformation measurement, and temperature measurement. The NTF instrument complex will be centered around four 32-bit, 1-microsecond-cycle-time central processing units connected in a multipoint-distributed network configuration. The principal activities to be supported by these computers are: (1) data base management and processing; (2) research measurement data acquisition and display; (3) tunnel and model control; and (4) process monitoring and communication control. The distributed network approach was chosen to modularize the functional software into definable and implementable parts by the various groups involved in the design and to permit use of similar hardware configurations to improve reliability and maintainability.

Guarino, J. F.↗

NASA NTRS1979

Development of Pulsed Processes for the Manufacture of Solar Cells

The development status of the process based upon ion implantation for the introduction of junctions and back surface fields is described. A process sequence is presented employing ion implantation and pulse processing. Efforts to improve throughout and descrease process element costs for furnace annealing are described. Design studies for a modular 3,000 wafer per hour pulse processor are discussed.

Source record↗

NASA NTRS1979

A flexible CAMAC based data system for Space Shuttle scientific instruments

An effort has been made within NASA to produce a low-cost modular system for implementation of Shuttle payloads based on the CAMAC standards for packaging and data transfer. A key element of such a modular system is a means for controlling the data system, collecting and processing the data for transmission to the ground, and issuing commands to the instrument either from the ground or based on the data collected. A description is presented of such a means based on a network of digital processors and CAMAC crate controllers, which allows for the implementation of instruments ranging from those requiring only a single CAMAC crate of functional modules and no data processing to ones requiring multiple crates and multiple data processors.

Ehrmann, C. H.↗