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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 37 records · Page 2

Large area CCD image sensors for scientific applications

The designs of the 512 x 512 pixel and 2048 x 2048 pixel CCD sensors developed for scientific imaging are described. Both sensors are manufactured using the three phase, three level polysilicon gate technology, and the architecture of the chips is series-parallel-series. The components of the two different on-chip amplifiers are examined. The sensors are thinned and operated in the back side illumination mode to ensure the highest quantum efficiency. The performances of a number of front side illuminated devices and two thinned rear illuminated chips are evaluated. It is observed that the sensors equal or exceed their proposed charge transfer efficiency of 0.99999, the noise level of 2 e- and 20 e- at 50 kp/s, the quantum efficiency of 40 percent at 400 microns and 70 percent at 700 microns, and of the well capacity of greater than 500 ke-/pixel.

Blouke, M. M.↗

ERAST: Scientific Applications and Technology Commercialization

This is a conference publication for an event designed to inform potential contractors and appropriate personnel in various scientific disciplines that the ERAST (Environmental Research Aircraft and Sensor Technology) vehicles have reached a certain level of maturity and are available to perform a variety of missions ranging from data gathering to telecommunications. There are multiple applications of the technology and a great many potential commercial and governmental markets. As high altitude platforms, the ERAST vehicles can gather data at higher resolution than satellites and can do so continuously, whereas satellites pass over a particular area only once each orbit. Formal addresses are given by Rich Christiansen, (Director of Programs, NASA Aerospace Technology Ent.), Larry Roeder, (Senior Policy Advisor, U.S. Dept. of State), and Dr. Marianne McCarthy, (DFRC Education Dept.). The Commercialization Workshop is chaired by Dale Tietz (President, New Vista International) and the Science Workshop is chaired by Steve Wegener, (Deputy Manager of NASA ERAST, NASA Ames Research Center.

Hunley, John D.↗

Deploying and Operating CephFS for Scientific Applications at Fermilab

Fermilab has been running a Ceph cluster in production for several years to support high-throughput scientific computing. Our primary use case is CephFS, which serves interactive data analysis workloads, with growing interest in using RGW for scalable object storage of scientific datasets. In this talk, we'll share lessons learned from successfully deploying and maintaining our Ceph cluster with cephadm, including challenges faced, performance tuning, and operational practices. We'll also present custom tools we've developed to streamline monitoring and management and discuss how Ceph fits into our broader storage architecture for large-scale scientific research.

Peisker, Alison [Fermilab]↗

Composable optimization and control toolkit for scientific applications

Applications of Artificial Intelligence (AI) and Machine Learning (ML) can improve the computational efficiency and scientific research output. In order to improve interoperability and reuse of AI/ML software, a composable approach is required. This talk presents a composable approach for scientific workflow development that allows seamless integration of various modules developed by independent researchers. These practices will reduce redundant software development by allowing re-use of workflow modules across projects, teams, departments and facilities. We will present three use cases that follow the composable approach namely, Scientific Optimization and Control Toolkit (SOCT), SciDAC QuantOm workflow, and JLab Nuclear Physics experimental workflows. This talk will dive deeper into SOCT and present the details of the composable code development for optimization and control algorithms using reinforcement learning.

Rajput, Kishansingh↗

Efficient Use of Distributed Systems for Scientific Applications

Distributed computing has been regarded as the future of high performance computing. Nationwide high speed networks such as vBNS are becoming widely available to interconnect high-speed computers, virtual environments, scientific instruments and large data sets. One of the major issues to be addressed with distributed systems is the development of computational tools that facilitate the efficient execution of parallel applications on such systems. These tools must exploit the heterogeneous resources (networks and compute nodes) in distributed systems. This paper presents a tool, called PART, which addresses this issue for mesh partitioning. PART takes advantage of the following heterogeneous system features: (1) processor speed; (2) number of processors; (3) local network performance; and (4) wide area network performance. Further, different finite element applications under consideration may have different computational complexities, different communication patterns, and different element types, which also must be taken into consideration when partitioning. PART uses parallel simulated annealing to partition the domain, taking into consideration network and processor heterogeneity. The results of using PART for an explicit finite element application executing on two IBM SPs (located at Argonne National Laboratory and the San Diego Supercomputer Center) indicate an increase in efficiency by up to 36% as compared to METIS, a widely used mesh partitioning tool. The input to METIS was modified to take into consideration heterogeneous processor performance; METIS does not take into consideration heterogeneous networks. The execution times for these applications were reduced by up to 30% as compared to METIS. These results are given in Figure 1 for four irregular meshes with number of elements ranging from 30,269 elements for the Barth5 mesh to 11,451 elements for the Barth4 mesh. Future work with PART entails using the tool with an integrated application requiring distributed systems. In particular this application, illustrated in the document entails an integration of finite element and fluid dynamic simulations to address the cooling of turbine blades of a gas turbine engine design. It is not uncommon to encounter high-temperature, film-cooled turbine airfoils with 1,000,000s of degrees of freedom. This results because of the complexity of the various components of the airfoils, requiring fine-grain meshing for accuracy. Additional information is contained in the original.

Taylor, Valerie↗

Engineering and Scientific Applications: Using MatLab(Registered Trademark) for Data Processing and Visualization

MatLab(R) (MATrix LABoratory) is a numerical computation and simulation tool that is used by thousands Scientists and Engineers in many cou ntries. MatLab does purely numerical calculations, which can be used as a glorified calculator or interpreter programming language; its re al strength is in matrix manipulations. Computer algebra functionalities are achieved within the MatLab environment using "symbolic" toolbo x. This feature is similar to computer algebra programs, provided by Maple or Mathematica to calculate with mathematical equations using s ymbolic operations. MatLab in its interpreter programming language fo rm (command interface) is similar with well known programming languag es such as C/C++, support data structures and cell arrays to define c lasses in object oriented programming. As such, MatLab is equipped with most ofthe essential constructs of a higher programming language. M atLab is packaged with an editor and debugging functionality useful t o perform analysis of large MatLab programs and find errors. We belie ve there are many ways to approach real-world problems; prescribed methods to ensure foregoing solutions are incorporated in design and ana lysis of data processing and visualization can benefit engineers and scientist in gaining wider insight in actual implementation of their perspective experiments. This presentation will focus on data processing and visualizations aspects of engineering and scientific applicati ons. Specifically, it will discuss methods and techniques to perform intermediate-level data processing covering engineering and scientifi c problems. MatLab programming techniques including reading various data files formats to produce customized publication-quality graphics, importing engineering and/or scientific data, organizing data in tabu lar format, exporting data to be used by other software programs such as Microsoft Excel, data presentation and visualization will be discussed. The presentation will emphasize creating practIcal scripts (pro grams) that extend the basic features of MatLab TOPICS mclude (1) Ma trix and vector analysis and manipulations (2) Mathematical functions (3) Symbolic calculations & functions (4) Import/export data files (5) Program lOgic and flow control (6) Writing function and passing parameters (7) Test application programs

Sen, Syamal K.↗

Software stewardship and advancement of a high-performance computing scientific application: QMCPACK

Here, we provide an overview of the software engineering efforts and their impact in QMCPACK, a production-level ab-initio Quantum Monte Carlo open-source code targeting high-performance computing (HPC) systems. Aspects included are: (i) strategic expansion of continuous integration (CI) targeting CPUs, using GitHub Actions own runners, and NVIDIA and AMD GPUs used in pre-exascale systems, (ii) incremental reduction of memory leaks using sanitizers, (iii) incorporation of Docker containers for CI and reproducibility, and (iv) refactoring efforts to improve maintainability, testing coverage, and memory lifetime management. We quantify the value of these improvements by providing metrics to illustrate the shift towards a predictive, rather than reactive, maintenance approach. Our goal, in documenting the impact of these efforts on QMCPACK, is to contribute to the body of knowledge on the importance of research software engineering (RSE) for the stewardship and advancement of community HPC codes to enable scientific discovery at scale.

97 MATHEMATICS AND COMPUTING↗

Non-smooth Bayesian optimization in tuning scientific applications

Tuning algorithmic parameters to optimize the performance of large, complicated computational codes is an important problem involving finding the optima and identifying regimes defined by non-smooth boundaries in black-box functions. Within the Bayesian optimization framework, the Gaussian process surrogate model produces smooth mean functions, but functions in the tuning problem are often non-smooth, which is exacerbated by the fact that we usually have limited sequential samples from the black-box function. Here, motivated by these issues encountered in tuning, we propose a novel Gaussian process model called a clustered Gaussian process (cGP), where the components are dynamically updated by clustering. In our studies, the performance of cGP can be better than stationary GPs in nearly 90% of the experiments and better than non-stationary GPs in nearly 70% of the repeated experiments while requiring less computational cost. cGP provides a novel approach for dynamic GP, computes more efficiently than recursive partitioning, and discovers non-smoothness regimes. We provide extensive experiments including high-performance computing (HPC) and industrial simulation functions to show the effectiveness of our methods.

97 MATHEMATICS AND COMPUTING↗

AUTOFLOW enhancements for documentation and maintenance of scientific applications

The use of the AUTOFLOW system is discussed in terms of improving automated documentation. Flowcharts produced by AUTOFLOW are considered to be much more meaningful than those produced manually in that they are accurate, present complete references between all transfer points, and graphically portray the logical flow by automatic rearrangement of those segments of the program that interact.

Goetz, M. A.↗

Civil and scientific applications of the geoid

SEASAT-A can be used for determining the geoid to much higher accuracy on a world wide basis and in a relatively short time. Two basic objectives can be considered: (1) determination of the geoid to at least 1 meter. This accuracy will satisfy most geodetic requirements for applications purposes; and (2) determination of the geoid to better than 1-meter an oceanographic objective required for measurement of sea surface topography and sea slope, quasi-stationary departure from the geoid, ocean circulation, air and sea interaction, etc. The geodesy objective in this case will be to define a reference equipotential surface as a means by which the oceanographic requirements can be achieved.

Mourad, A. G.↗

Caltech/JPL Conference on Image Processing Technology, Data Sources and Software for Commercial and Scientific Applications

Recent advances in image processing and new applications are presented to the user community to stimulate the development and transfer of this technology to industrial and commercial applications. The Proceedings contains 37 papers and abstracts, including many illustrations (some in color) and provides a single reference source for the user community regarding the ordering and obtaining of NASA-developed image-processing software and science data.

Redmann, G. H.↗

Evaluation of RCA thinned buried channel charge-coupled devices /CCDs/ for scientific applications

An experimental version of a thinned illuminated buried-channel 512 x 320 pixel CCD with reduced amplifier input capacitance has been produced which is characterized by lower readout noise. Changes made to the amplifier are discussed, and readout noise measurements obtained by several different techniques are presented. The single energetic electron response of the CCD in the electron-bombarded mode and the single 5.9 keV X-ray pulse height distribution are reported. Results are also given on the dark current versus temperature and the spatial frequency response as a function of signal level.

Zucchino, P.↗