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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 397 records · Page 22

Volumetric additive manufacturing via tomographic reconstruction

Additive manufacturing promises enormous geometrical freedom and the potential to combine materials for complex functions. The speed, geometry, and surface quality limitations of additive processes are linked to their reliance on material layering. We demonstrated concurrent printing of all points within a three-dimensional object by illuminating a rotating volume of photosensitive material with a dynamically evolving light pattern. We printed features as small as 0.3 millimeters in engineering acrylate polymers and printed soft structures with exceptionally smooth surfaces into a gelatin methacrylate hydrogel. Our process enables us to construct components that encase other preexisting solid objects, allowing for multimaterial fabrication. We developed models to describe speed and spatial resolution capabilities and demonstrated printing times of 30 to 120 seconds for diverse centimeter-scale objects.

42 ENGINEERING↗

Developing a novel hierarchical approach for multiscale structural reliability predictions for ultra-high consequence applications

Microstructural variabilities are among the predominant sources of uncertainty in structural performance and reliability. We seek to develop efficient algorithms for multiscale calcu- lations for polycrystalline alloys such as aluminum alloy 6061-T6 in environments where ductile fracture is the dominant failure mode. Our approach employs concurrent multiscale methods, but does not focus on their development. They are a necessary but not sufficient ingredient to multiscale reliability predictions. We have focused on how to efficiently use concurrent models for forward propagation because practical applications cannot include fine-scale details throughout the problem domain due to exorbitant computational demand. Our approach begins with a low-fidelity prediction at the engineering scale that is sub- sequently refined with multiscale simulation. The results presented in this report focus on plasticity and damage at the meso-scale, efforts to expedite Monte Carlo simulation with mi- crostructural considerations, modeling aspects regarding geometric representation of grains and second-phase particles, and contrasting algorithms for scale coupling.

36 MATERIALS SCIENCE↗

Scalable Control Co-design for Resilient-by-Design Cyber Physical Systems

Critical infrastructure networks, such as power and transportation networks, are often modelled as cyber-physical systems. With ever increasing complexity of these systems, there is a need for newer and more relevant metrics and design tools that will co-optimize the physical system components and control policies to guarantee resilience against cyber and natural threats. To this end, a simulation-based control co-design computational framework that will concurrently determine the system and control parameters of a cyber-physical system to meet pre-specified resilience, operational and economic objectives has been developed. The capabilities of the developed co-design engine are demonstrated by designing the physical components and control parameters of a microgrid system that will meet its resiliency objectives when subjected to various cyber and physical threats.

42 ENGINEERING↗

Landrush: Rethinking In-Situ Analysis for GPGPU Workflows

In-situ analysis on the output data of scientific simulations has been made necessary by ever-growing output data volumes and increasing costs of data movement as supercomputing is moving towards exascale. With hardware accelerators like GPUs becoming increasingly common in high end machines, new opportunities arise to co-locate scientific simulations and online analysis performed on the scientific data generated by the simulations. However, the asynchronous nature of GPGPU programming models and the limited context-switching capabilities on the GPU pose challenges to co-locating the scientific simulation and analysis on the same GPU. This paper dives deeper into these challenges to understand how best to co-locate analysis with scientific simulations on the GPUs in HPC clusters. Specifically, our 'Landrush' approach to GPU sharing proposes a solution that utilizes idle cycles on the GPU to provide an improved time-to-answer, that is, the total time to run the scientific simulation and analysis of the generated data. Landrush is demonstrated with experimental results obtained from leadership high-end applications on ORNL's Titan supercomputer, which show that (i) GPU-based scientific simulations have varying degrees of idle cycles to afford useful analysis task co-location, and (ii) the inability to context switch on the GPU at instruction granularity can be overcome by careful control of the analysis kernel launches and software-controlled early completion of analysis kernel executions. Results show that Landrush is superior in terms of time-to-answer compared to serially running simulations followed by analysis or by relying on the GPU driver and hardwired thread dispatcher to run analysis concurrently on a single GPU.

Computer Science↗

Co-Optima Stakeholder Listening Day Summary Report

On June 16–17, 2015, the U.S. Department of Energy (DOE) convened the Optima Stakeholder Listening ay to share information on an emerging effort to concurrently investigate the optimization of fuels and vehicles. At the time of the stakeholder listening day, this effort was referred to as “Optima.” The revised name of the effort is Co-Optimization of Fuels & Engines (Co-Optima). The effort and the listening day will use the term “Co-Optima” hereafter in this report.Co-Optima officially began in FY 2016 and is a collaboration of the DOE Vehicle Technologies Office, Bioenergy Technologies Office, and the DOE national laboratories. In FY 2015, DOE invited industry stakeholders to the listening day to obtain critical input on the opportunities and challenges of this effort. The meeting was held in Golden, Colorado, and hosted by the National Renewable Energy Laboratory.

33 ADVANCED PROPULSION SYSTEMS↗

Coverage Metrics for Model Checking

When using model checking to verify programs in practice, it is not usually possible to achieve complete coverage of the system. In this position paper we describe ongoing research within the Automated Software Engineering group at NASA Ames on the use of test coverage metrics to measure partial coverage and provide heuristic guidance for program model checking. We are specifically interested in applying and developing coverage metrics for concurrent programs that might be used to support certification of next generation avionics software.

Penix, John↗

Planning as an Iterative Process

Activity planning for missions such as the Mars Exploration Rover mission presents many technical challenges, including oversubscription, consideration of time, concurrency, resources, preferences, and uncertainty. These challenges have all been addressed by the research community to varying degrees, but significant technical hurdles still remain. In addition, the integration of these capabilities into a single planning engine remains largely unaddressed. However, I argue that there is a deeper set of issues that needs to be considered namely the integration of planning into an iterative process that begins before the goals, objectives, and preferences are fully defined. This introduces a number of technical challenges for planning, including the ability to more naturally specify and utilize constraints on the planning process, the ability to generate multiple qualitatively different plans, and the ability to provide deep explanation of plans.

Smith, David E.↗

Model Based Mission Assurance: Emerging Opportunities for Robotic Systems

The emergence of Model Based Systems Engineering (MBSE) in a Model Based Engineering framework has created new opportunities to improve effectiveness and efficiencies across the assurance functions. The MBSE environment supports not only system architecture development, but provides for support of Systems Safety, Reliability and Risk Analysis concurrently in the same framework. Linking to detailed design will further improve assurance capabilities to support failures avoidance and mitigation in flight systems. This also is leading new assurance functions including model assurance and management of uncertainty in the modeling environment. Further, the assurance cases, a structured hierarchal argument or model, are emerging as a basis for supporting a comprehensive viewpoint in which to support Model Based Mission Assurance (MBMA).

Mission Assurance↗

Precipitation of calcium carbonate and calcium phosphate under diffusion controlled mixing

Multi-component mineral precipitation in porous, subsurface environments is challenging to simulate or engineer when in situ reactant mixing is controlled by diffusion. In contrast to well-mixed systems, the conditions that favor mineral precipitation in porous media are distributed along chemical gradients, which evolve spatially due to concurrent mineral precipitation and modification of solute transport in the media. The resulting physical and chemical characteristics of a mixing/precipitation zone are a consequence of coupling between transport and chemical processes, and the distinctive properties of individual chemical systems. We examined the spatial distribution of precipitates formed in “double diffusion” columns for two chemical systems, calcium carbonate and calcium phosphate. Polyacrylamide hydrogel was used as a low permeability, high porosity medium to maximize diffusive mixing and minimize pressure- and density-driven flow between reactant solutions. In the calcium phosphate system, multiple, visually dense and narrow bands of precipitates were observed that were reminiscent of previously reported Liesegang patterns. In the calcium carbonate system, wider precipitation zones characterized by more sparse distributions of precipitates and a more open channel structure were observed. In both cases, formation of precipitates inhibited, but did not necessarily eliminate, continued transport and mixing of the reactants. A reactive transport model with fully implicit coupling between diffusion, chemical speciation and precipitation kinetics, but where explicit details of nucleation processes were neglected, was able to qualitatively simulate properties of the precipitation zones. The results help to illustrate how changes in the physical properties of a precipitation zone depend on coupling between diffusion-controlled reactant mixing and chemistry-specific details of precipitation kinetics.

54 ENVIRONMENTAL SCIENCES↗

Rubisco regulation in response to altered carbon status in the cyanobacterium Synechococcus elongatus PCC 7942

Abstract Photosynthetic organisms possess a variety of mechanisms to achieve balance between absorbed light (source) and the capacity to metabolically utilize or dissipate this energy (sink). While regulatory processes that detect changes in metabolic status/balance are relatively well studied in plants, analogous pathways remain poorly characterized in photosynthetic microbes. Here, we explored systemic changes that result from alterations in carbon availability in the model cyanobacterium Synechococcus elongatus PCC 7942 by taking advantage of an engineered strain where influx/efflux of a central carbon metabolite, sucrose, can be regulated experimentally. We observed that induction of a high-flux sucrose export pathway leads to depletion of internal carbon storage pools (glycogen) and concurrent increases in estimates of photosynthetic activity. Further, a proteome-wide analysis and fluorescence reporter-based analysis revealed that upregulated factors following the activation of the metabolic sink are concentrated on ribulose-1,5-bisphosphate carboxylase-oxygenase (Rubisco) and auxiliary modules involved in Rubisco maturation. Carboxysome number and Rubisco activity also increased following engagement of sucrose secretion. Conversely, reversing the flux of sucrose by feeding exogenous sucrose through the heterologous transporter resulted in increased glycogen pools, decreased Rubisco abundance, and carboxysome reorganization. Our data suggest that Rubisco activity and organization are key variables connected to regulatory pathways involved in metabolic balancing in cyanobacteria.

Plant Sciences↗

T-FSM: A Scalable Distributed Task-Based System for Frequent Subgraph Pattern Mining from a Big Graph

Finding frequent subgraph patterns in a big graph is an important problem with many applications such as classifying chemical compounds and building indexes to speed up graph queries. Since this problem is NP-hard, some recent parallel and distributed systems have been developed to accelerate the mining. However, they often have a huge memory cost, very long running time, suboptimal load balancing, poor scale-out capability, and possibly inaccurate results. In this article, we propose an efficient system called T-FSM for parallel mining of frequent subgraph patterns in a big graph. T-FSM supports a new anti-monotonic frequentness measure called Fraction-Score, which is more accurate than the widely used MNI measure. The execution engine of T-FSM supports both intra-machine parallelism and inter-machine parallelism. For intra-machine parallelism, T-FSM adopts a novel task-based execution model to ensure high multithreading concurrency, bounded memory consumption, and effective load balancing. For inter-machine parallelism, T-FSM ensures good scale-out performance with a lightweight pattern rebalancing approach that reduces workload skewness of pattern evaluations among machines. To avoid recomputing the contexts for migrated patterns, we design a novel context cache table to support concurrent and asynchronous requesting and caching of remote context data, which can timely evict and garbage collect used pattern contexts that are no longer needed to keep memory consumption bounded. Extensive experiments show that T-FSM is orders of magnitude faster than existing state-of-the-art parallel systems (more than 10×, 51×, 131×, 55× speedup over ScaleMine, DistGraph, Pangolin and Peregrine, respectively) and distributed systems (more than 42× and 88× over ScaleMine and DistGraph, respectively) for frequent subgraph pattern mining, and it scales out satisfactorily to 512 CPU cores on the Polaris supercomputer at Argonne National Laboratory.

97 MATHEMATICS AND COMPUTING↗

The Application of New Software Technology to the Architecture of the National Cycle Program

As part of the Numerical Propulsion System Simulation (NPSS) effort of NASA Lewis in conjunction with the United States aeropropulsion industry, a new system simulation framework, the National Cycle Program (NCP), capable of combining existing empirical engine models with new detailed component-based computational models is being developed. The software architecture of the NCP program involves a generalized object- oriented framework and a base-set of engine component models along with supporting tool kits which will support engine simulation in a distributed environment. As the models are extended to contain two and three dimensions the computing load increases rapidly and it is intended that this load be distributed across multiple work stations executing concurrently in order to get acceptably fast results. The research carried out was directed toward performance analysis of the distributed object system. More specifically, the performance of the actor-based distributed object design I created earlier was desired. To this end, the research was directed toward the design and implementation of suitable performance-analysis techniques and software to demonstrate those techniques. There were three specific results which are reported in two separate reports submitted separately as NASA Technical Memoranda. The results are: (1) Design, implementation, and testing of a performance analysis program for a set of active objects (actor based objects) which allowed the individual actors to be assigned to arbitrary processes on an arbitrary set of machines. (2) The global-balance-equation approach has the fundamental limitation that the number of equations increases exponentially with the number of actors. Hence, unlike many approximate approaches to this problem, the nearest-neighbor approach allows checking of the solution and an estimate of the error. The technique was demonstrated in a prototype analysis program as part of this research. The results of the program were checked against the global-balance solution discussed above. Late during the grant, a much better approximation was developed and this is discussed in result below. As a consequence, a proposal was submitted to continue the research by developing the new approximation including development of a complete program from the prototype. (3) The source of approximation in the nearest-neighbor algorithm is the requirement for estimating some joint probabilities from some marginal distributions. A completely ad hoc estimate was used in the prototype.

Schoeffler, James D.↗

Monitoring Java Programs with Java PathExplorer

We present recent work on the development Java PathExplorer (JPAX), a tool for monitoring the execution of Java programs. JPAX can be used during program testing to gain increased information about program executions, and can potentially furthermore be applied during operation to survey safety critical systems. The tool facilitates automated instrumentation of a program's late code which will then omit events to an observer during its execution. The observer checks the events against user provided high level requirement specifications, for example temporal logic formulae, and against lower level error detection procedures, for example concurrency related such as deadlock and data race algorithms. High level requirement specifications together with their underlying logics are defined in the Maude rewriting logic, and then can either be directly checked using the Maude rewriting engine, or be first translated to efficient data structures and then checked in Java.

Havelund, Klaus↗

Rapid Development of Instrument Thermal Models: Perspectives and Guidelines from NASA Goddard’s Instrument Design Laboratory

The Instrument Design Laboratory (IDL), part of NASA Goddard Space Flight Center’s Integrated Design Center (IDC), is a concurrent and collaborative environment which allows for rapid development of science instrumentation concepts within the span of less than two weeks. Science goals set by a Principal Investigator from government, industry or academia are translated into engineering requirements, from which a team of engineers spanning multiple disciplines use an established study process and a suite of analysis tools to work towards an instrument point design. As part of this process, a staff thermal engineer is tasked with designing a thermal control system which meets all incoming thermal requirements, while iterating real-time with other subsystems to ensure compatibility and functionality as a completed system. Thermal engineers on spaceflight projects typically have weeks or months to develop thermal models. However, the severe time limitation in this conceptual study setting makes thermal design particularly difficult, as rapid thermal modeling solely over the span of a few days is required to develop the instrument thermal design and understand the performance over its intended mission, especially if the instrument concept contains multiple thermal challenges such as dynamic environments or high heat dissipating components. In this paper, the authors provide a condensed guide for the most efficient ways to develop thermal models and conduct thermal analysis within the span of one-to-two weeks, as informed by decades of design experience and best practices in the IDL. The authors also focus on quick methods for determining worst-case thermal environments, deciding which modeling details are essential at this early phase, and quantifying the engineering resources necessary for thermal control. This paper concludes with specific thermal design tips for different instrument types across the electromagnetic spectrum.

Kan Yang↗

Multidisciplinary design optimization in Architecture, Engineering, and Construction: a detailed review and call for collaboration

The design of buildings has become a complex and multidisciplinary problem involving multiple conflicting objectives as architects and designers address competing technical, economic, environmental, and societal concerns. This has been driving research in Architecture, Engineering, and Construction (AEC) toward rigorous multidisciplinary decision-making frameworks that generate and evaluate numerous design alternatives using multi-objective optimization in concert with simulation and analysis models of varying fidelity and computational expense. While such frameworks are well known and widely employed in the aerospace and systems engineering domains, efforts by design professionals and researchers in the AEC field are scattered at best. In this paper, we provide a detailed review of recent developments in optimization frameworks in the AEC field and subsequently highlight how such developments are largely compartmentalized into separate domains such as structural, energy, daylighting, and other performance factors. Herein, we further discuss the technical challenges involved in concurrent coupled multidisciplinary design optimization (MDO) in the AEC field such as interoperability issues between Building Information Modeling (BIM) environments, analysis/simulation tools, and optimization frameworks. We conclude by outlining research needed for more unified modeling and simulation-based optimization frameworks to aid in complex and multidisciplinary building design processes. We also highlight the need for the identification and development of multi-fidelity simulation tools for use across multiple design phases. As such, this paper contributes a novel roadmap to leverage aerospace and systems engineering research in MDO into the field of AEC, along with a call for researchers in the MDO community to seek collaborations in AEC field.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Bayesian calibration of stochastic agent based model via random forest

SAND2024-11403O The Bayesian Calibration of Stochastic Agent-based Model via Random Forest is a code that was developed in concurrence with an article by the same name that was written for a journal. The code reproduces simulation results and plots from the article. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

SciDAC↗

Report of the 2014 Programming Models and Environments Summit

Programming models and environments play the essential roles in high performance computing of enabling the conception, design, implementation and execution of science and engineering application codes. Programmer productivity is strongly influenced by the effectiveness of our programming models and environments, as is software sustainability since our codes have lifespans measured in decades, so the advent of new computing architectures, increased concurrency, concerns for resilience, and the increasing demands for high-fidelity, multi-physics, multi-scale and data-intensive computations mean that we have new challenges to address as part of our fundamental R&D requirements. Fortunately, we also have new tools and environments that make design, prototyping and delivery of new programming models easier than ever. The combination of new and challenging requirements and new, powerful toolsets enables significant synergies for the next generation of programming models and environments R&D. This report presents the topics discussed and results from the 2014 DOE Office of Science Advanced Scientific Computing Research (ASCR) Programming Models & Environments Summit, and subsequent discussions among the summit participants and contributors to topics in this report.

97 MATHEMATICS AND COMPUTING↗

Regenerative life support system research

Sections on modeling, experimental activities during the grant period, and topics under consideration for the future are contained. The sessions contain discussions of: four concurrent modeling approaches that were being integrated near the end of the period (knowledge-based modeling support infrastructure and data base management, object-oriented steady state simulations for three concepts, steady state mass-balance engineering tradeoff studies, and object-oriented time-step, quasidynamic simulations of generic concepts); interdisciplinary research activities, beginning with a discussion of RECON lab development and use, and followed with discussions of waste processing research, algae studies and subsystem modeling, low pressure growth testing of plants, subsystem modeling of plants, control of plant growth using lighting and CO2 supply as variables, search for and development of lunar soil simulants, preliminary design parameters for a lunar base life support system, and research considerations for food processing in space; and appendix materials, including a discussion of the CELSS Conference, detailed analytical equations for mass-balance modeling, plant modeling equations, and parametric data on existing life support systems for use in modeling.

Source record↗