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Lost in Cloud

Cloud computing can reduce cost significantly because businesses can share computing resources. In recent years Small and Medium Businesses (SMB) have used Cloud effectively for cost saving and for sharing IT expenses. With the success of SMBs, many perceive that the larger enterprises ought to move into Cloud environment as well. Government agency s stove-piped environments are being considered as candidates for potential use of Cloud either as an enterprise entity or pockets of small communities. Cloud Computing is the delivery of computing as a service rather than as a product, whereby shared resources, software, and information are provided to computers and other devices as a utility over a network. Underneath the offered services, there exists a modern infrastructure cost of which is often spread across its services or its investors. As NASA is considered as an Enterprise class organization, like other enterprises, a shift has been occurring in perceiving its IT services as candidates for Cloud services. This paper discusses market trends in cloud computing from an enterprise angle and then addresses the topic of Cloud Computing for NASA in two possible forms. First, in the form of a public Cloud to support it as an enterprise, as well as to share it with the commercial and public at large. Second, as a private Cloud wherein the infrastructure is operated solely for NASA, whether managed internally or by a third-party and hosted internally or externally. The paper addresses the strengths and weaknesses of both paradigms of public and private Clouds, in both internally and externally operated settings. The content of the paper is from a NASA perspective but is applicable to any large enterprise with thousands of employees and contractors.

Maluf, David A.↗

High-Speed Multiprocessing For Engine Simulation

Parallel microprocessors have computational power and speed for realistic simulations. Interactive information bus links front-end processor and computational processors. Real-time information bus links real-time extension processor and pre-processors. Computational processor and preprocessor communicate through shared memory. System used to simulate small turboshaft engine to demonstrate potential of multiprocessing in such applications. Real-time simulations aid development of new digital engine controls enabling testing of hardware and software under realistic conditions.

Milner, Edward J.↗

Impact of Sr-Containing Secondary Phases on Oxide Conductivity in Solid-Oxide Electrolyzer Cells

Solid-oxide electrolyzer cells (SOECs) based on a yttria-stabilized zirconia (YSZ) oxide electrolyte produce hydrogen from water with the assistance of excess thermal energy; however, Sr diffusion within the Gd-doped CeO 2 (GDC) barrier layer during processing or operation can lead to the formation of unwanted secondary phases such as SrO and SrZrO 3 . Here, to establish and compare the degree of impact of these phases on SOEC performance, we conduct first-principles calculations to study their bulk oxide conductivities and compare them to that of the YSZ electrolyte. We find that SrO has a low conductivity arising from the poor mobility and low concentration of mobile oxygen vacancies, and its presence in SOECs should therefore be avoided. SrZrO 3 also has a lower oxide conductivity than YSZ; however, this discrepancy is primarily due to lower vacancy concentrations rather than low mobility. We find that sufficient levels of Y-doping on the Zr site can increase oxygen vacancy concentrations in SrZrO 3 to achieve an oxide ionic conductivity on par with that of YSZ, thereby mitigating any potential deleterious effect on transport performance. Energy-dispersive X-ray spectroscopy confirms that Y is the most common minority element present in SrZrO 3 forming near the GDC–YSZ interface, alleviating concerns regarding the impact of SrZrO 3 on device performance. These results from our combined computational–experimental analysis can inform future engineering strategies designed to limit the detrimental effects of Sr-induced secondary phase formation on SOEC performance.

08 HYDROGEN↗

Networked HIL Simulation System for Modeling Large-scale Power Systems

This paper presents a networked hardware-in-the-loop (HIL) simulation system for modeling large-scale power systems. Researchers have developed many HIL test systems for power systems in recent years. Those test systems can model both microsecond-level dynamic responses of power electronic systems and millisecond-level transients of transmission and distribution grids. By integrating individual HIL test systems into a network of HIL test systems, we can create large-scale power grid digital twins with flexible structures at required modeling resolution that fits for a wide range of system operating conditions. This will not only significantly reduce the need for field tests when developing new technologies but also greatly shorten the model development cycle. In this paper, we present a networked OPAL-RT based HIL test system for developing transmission-distribution coordinative Volt-VAr regulation technologies as an example to illustrate system setups, communication requirements among different HIL simulation systems, and system connection mechanisms. Impacts of communication delays, information exchange cycles, and computing delays are illustrated. Simulation results show that the performance of a networked HIL test system is satisfactory.

Xie, Fuhong↗

QSCOUT Progress Report, June 2022 [Quantum Scientific Computing Open User Testbed]

Quantum information processing has reached an inflection point, transitioning from proof-of-principle scientific experiments to small, noisy quantum processors. To accelerate this process and eventually move to fault-tolerant quantum computing, it is necessary to provide the scientific community with access to whitebox testbed systems. The Quantum Scientific Computing Open User Testbed (QSCOUT) provides scientists unique access to an innovative system to help advance quantum computing science.

97 MATHEMATICS AND COMPUTING↗

Explicit block encodings of boundary value problems for many-body elliptic operators

Simulation of physical systems is one of the most promising use cases of future digital quantum computers. In this work we systematically analyze the quantum circuit complexities of block encoding the discretized elliptic operators that arise extensively in numerical simulations for partial differential equations, including high-dimensional instances for many-body simulations. When restricted to rectangular domains with separable boundary conditions, we provide explicit circuits to block encode the many-body Laplacian with separable periodic, Dirichlet, Neumann, and Robin boundary conditions, using standard discretization techniques from low-order finite difference methods. To obtain high-precision, we introduce a scheme based on periodic extensions to solve Dirichlet and Neumann boundary value problems using a high-order finite difference method, with only a constant increase in total circuit depth and subnormalization factor. We then present a scheme to implement block encodings of differential operators acting on more arbitrary domains, inspired by Cartesian immersed boundary methods. We then block encode the many-body convective operator, which describes interacting particles experiencing a force generated by a pair-wise potential given as an inverse power law of the interparticle distance. This work provides concrete recipes that are readily translated into quantum circuits, with depth logarithmic in the total Hilbert space dimension, that block encode operators arising broadly in applications involving the quantum simulation of quantum and classical many-body mechanics.

Kharazi, Tyler [University of California, Berkeley↗

Spectral transformation in the SOFI complex for processing photographic images on the ES computer, part 1

A description is given of three programs catalogued in the form of object modules in the library of a system for processing photographic images computer. PFT is the subprogram of the multi-dimensional BPF of real-valued information, in the operative computer memory. INRECO is a subprogram-interface between the real and complex formats for representing two-dimensional spectra and images. FFT2 is a subprogram for calculating the correlation functions of the image using the previous subprograms.

Debabov, A. S.↗

Prioritized LT Codes

The original Luby Transform (LT) coding scheme is extended to account for data transmissions where some information symbols in a message block are more important than others. Prioritized LT codes provide unequal error protection (UEP) of data on an erasure channel by modifying the original LT encoder. The prioritized algorithm improves high-priority data protection without penalizing low-priority data recovery. Moreover, low-latency decoding is also obtained for high-priority data due to fast encoding. Prioritized LT codes only require a slight change in the original encoding algorithm, and no changes at all at the decoder. Hence, with a small complexity increase in the LT encoder, an improved UEP and low-decoding latency performance for high-priority data can be achieved. LT encoding partitions a data stream into fixed-sized message blocks each with a constant number of information symbols. To generate a code symbol from the information symbols in a message, the Robust-Soliton probability distribution is first applied in order to determine the number of information symbols to be used to compute the code symbol. Then, the specific information symbols are chosen uniform randomly from the message block. Finally, the selected information symbols are XORed to form the code symbol. The Prioritized LT code construction includes an additional restriction that code symbols formed by a relatively small number of XORed information symbols select some of these information symbols from the pool of high-priority data. Once high-priority data are fully covered, encoding continues with the conventional LT approach where code symbols are generated by selecting information symbols from the entire message block including all different priorities. Therefore, if code symbols derived from high-priority data experience an unusual high number of erasures, Prioritized LT codes can still reliably recover both high- and low-priority data. This hybrid approach decides not only "how to encode" but also "what to encode" to achieve UEP. Another advantage of the priority encoding process is that the majority of high-priority data can be decoded sooner since only a small number of code symbols are required to reconstruct high-priority data. This approach increases the likelihood that high-priority data is decoded first over low-priority data. The Prioritized LT code scheme achieves an improvement in high-priority data decoding performance as well as overall information recovery without penalizing the decoding of low-priority data, assuming high-priority data is no more than half of a message block. The cost is in the additional complexity required in the encoder. If extra computation resource is available at the transmitter, image, voice, and video transmission quality in terrestrial and space communications can benefit from accurate use of redundancy in protecting data with varying priorities.

Woo, Simon S.↗

Modeling the performance of the human (pilot) interaction in a synthetic flight domain: Information theoretic approach

Current advances in computing technology are devoid of formal methods that describe the theories of how information is shared between humans and machines. Specifically, in the domain of human-machine interaction, a common mathematical foundation is lacking. The aim of this paper is to propose a formal method of human-machine (H-M) interaction paradigm from the information view point. The methods presented are interpretation- and context-free and can be used both in experimental analysis as well as in modeling problems.

Ntuen, Celestine A.↗

More About Software for No-Loss Computing

A document presents some additional information on the subject matter of "Integrated Hardware and Software for No- Loss Computing" (NPO-42554), which appears elsewhere in this issue of NASA Tech Briefs. To recapitulate: The hardware and software designs of a developmental parallel computing system are integrated to effectuate a concept of no-loss computing (NLC). The system is designed to reconfigure an application program such that it can be monitored in real time and further reconfigured to continue a computation in the event of failure of one of the computers. The design provides for (1) a distributed class of NLC computation agents, denoted introspection agents, that effects hierarchical detection of anomalies; (2) enhancement of the compiler of the parallel computing system to cause generation of state vectors that can be used to continue a computation in the event of a failure; and (3) activation of a recovery component when an anomaly is detected.

Edmonds, Iarina↗

FAST-1.2 User Installation and Verification Guide: Developed Under NQA-1-2017

The purpose of this document is to provide the user information about the installation of Fuel Analysis for Steady state and Transient (FAST)-1.2 on their computers or servers. General information about the code and supported operating systems is described in Section 1.0. Self-service oriented FAST-1.2 software licensing steps are described in Section 2.0. An installation verification test suite is provided with FAST-1.2 and described in Section 3.0. A convenience script for converting Fuel Rod Analysis Program – Constant (FRAPCON) to FAST inputs is discussed in Section 4.0. FAST-1.2 was developed and released under a software quality assurance program based upon NQA-1-2017 at Pacific Northwest National Laboratory (PNNL). FAST-1.2 is the latest baseline code. The installation verification test suite contains both steady state and transient Anticipated Operation Occurrences (AOOs), accident conditions, such as Reactivity Initiated Accidents (RIAs) and Loss of Coolant Accidents (LOCAs).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Non -degenerate marginal-likelihood calibration with application to quantum characterization

Here, we propose a marginal likelihood strategy within the Kennedy-O’Hagan (KOH) Bayesian framework, where a Gaussian process (GP) models the discrepancy between a physical system and its simulator. Our approach introduces a novel marginalized likelihood by integrating out the degenerate eigenspace of the covariance matrix, rather than approximating the original likelihood. Unlike approximation methods that compromise accuracy for computational efficiency, our method defines an exact likelihood—distinct from the original but preserving all relevant information. This formulation achieves computational efficiency and stability, even for large datasets where the covariance matrix nears degeneracy. Applied to the characterization of a superconducting quantum device at Lawrence Livermore National Laboratory, the approach enhances the predictive accuracy of the Lindblad master equations for modeling Ramsey measurement data by effectively quantifying uncertainties consistent with the quantum data.

general physics↗

Asynchronous GPU-based DEM solver embedded in commercial CFD software with polyhedral mesh support

A novel graphical processing unit-based discrete element method solver is introduced to improve stability, performance, and provide seamless integration into commercial or open-source computational fluid dynamics software. A key innovation is eliminating a need for network communication between solvers, which was previously required for cross-platform coupling. This is accomplished by a direct coupling method that employs dynamic-linked libraries. Furthermore, the solver optimizes memory usage by streamlining the particle-cell search algorithm by eliminating the cells' searching grid. This ensures the solver is compatible with a wide range of mesh types, providing high geometric flexibility. The approach simplifies the simulation process by directly incorporating computational fluid dynamics mesh information into the discrete element method solver. The performance analysis indicates about sixteen times boost in computational speed compared to benchmark central processing unit-based solvers. Finally, the solver's compatibility with polyhedral meshes, a vital advantage for complex geometries, is tested against a referenced study regarding the simulation of an immersed-tube fluidized bed.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Computing partition functions in the one-clean-qubit model

We present a method to approximate partition functions of quantum systems using mixed-state quantum computation. For positive-semidefinite Hamiltonians, our method has an expected running-time that is almost linear in [M/( ε rel Z )] 2 , where M is the dimension of the quantum system, Z is the partition function, and ε rel is the relative precision. It is based on approximations of the exponential operator as linear combinations of certain operators related to block-encoding of Hamiltonians or Hamiltonian evolutions. The trace of each operator is estimated using a standard algorithm in the one-clean-qubit model. For large values of Z , our method may run faster than exact classical methods, whose complexities are polynomial in M . We also prove that a version of the partition function estimation problem within additive error is complete for the so-called DQC1 complexity class, suggesting that our method provides a superpolynomial speedup for certain parameter values. Overall, to attain a desired relative precision, we develop a classical procedure based on a sequence of approximations within predetermined additive errors that may be of independent interest.

97 MATHEMATICS AND COMPUTING↗

A computer program for calculating symmetrical aerodynamic characteristics and lateral-directional stability derivatives of wing-body combinations with blowing jets

The necessary information for using a computer program to calculate the aerodynamic characteristics under symmetrical flight conditions and the lateral-directional stability derivatives of wing-body combinations with upper-surface-blowing (USB) or over-wing-blowing (OWB) jets are described. The following new features were added to the program: (1) a fuselage of arbitrary body of revolution has been included. The effect of wing-body interference can now be investigated, and (2) all nine lateral-directional stability derivatives can be calculated. The program is written in FORTRAN language and runs on CDC Cyber 175 and Honeywell 66/60 computers.

Lan, C. E.↗

Smart connected worker edge platform for smart manufacturing: Part 1—Architecture and platform design

Abstract The challenge of sustainably producing goods and services for healthy living on a healthy planet requires simultaneous consideration of economic, societal, and environmental dimensions in manufacturing. Enabling technology for data driven manufacturing paradigms like Smart Manufacturing (a.k.a. Industry 4.0) serve as the technological backbone from which sustainable approaches to manufacturing can be implemented. Unfortunately, these technologies are typically associated with broader and deeper factory automation that is often too expensive and complex for the small and medium sized manufacturers (SMMs) that comprise the majority of manufacturing business in the USA and for whom their most valuable asset are the people whose jobs automation while replace. This paper describes an edge intelligent platform to integrate internet‐of‐things technologies with computing hardware, software, computational workflows for machine learning, and data ingestion, enabling SMMs to transition into smart manufacturing paradigms by leveraging the intelligence of their people. The platform leverages consumer grade electronics and sensors (affordable and portable), customized software with open source software packages (accessible), and existing communication network infrastructures (scalable). The software systems are implemented via Kubernetes orchestration of Docker containerization to ensure scalability and programmability. The platform is adaptive via computational workflow engines that produce information from data by processing with low‐cost edge computing devices while efficiently accessing resources of cloud servers as needed. The proposed edge platform connects workers to technological resources that provide computational intelligence (i.e., silicon‐based sensing and computation for data collection and contextualization) to enable decision making at the edge of advanced manufacturing.

Kim, Yoon G.↗