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At least 199 records · Page 11

The microcomputer workstation - An alternate hardware architecture for remotely sensed image analysis

Difficulties regarding the digital image analysis of remotely sensed imagery can arise in connection with the extensive calculations required. In the past, an expensive large to medium mainframe computer system was needed for performing these calculations. For image-processing applications smaller minicomputer-based systems are now used by many organizations. The costs for such systems are still in the range from $100K to $300K. Recently, as a result of new developments, the use of low-cost microcomputers for image processing and display systems appeared to have become feasible. These developments are related to the advent of the 16-bit microprocessor and the concept of the microcomputer workstation. Earlier 8-bit microcomputer-based image processing systems are briefly examined, and a computer workstation architecture is discussed. Attention is given to a microcomputer workstation developed by Stanford University, and the design and implementation of a workstation network.

Erickson, W. K.↗

A spacecraft computer repairable via command.

The MULTIPAC is a central data system developed for deep-space probes with the distinctive feature that it may be repaired during flight via command and telemetry links by reprogramming around the failed unit. The computer organization uses pools of identical modules which the program organizes into one or more computers called processors. The interaction of these modules is dynamically controlled by the program rather than hardware. In the event of a failure, new programs are entered which reorganize the central data system with a somewhat reduced total processing capability aboard the spacecraft. Emphasis is placed on the evolution of the system architecture and the final overall system design rather than the specific logic design.

Fimmel, R. O.↗

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗

Tree tensor network hierarchical equations of motion based on time-dependent variational principle for efficient open quantum dynamics in structured thermal environments

In this work, we introduce an efficient method, TTN-HEOM, for exactly calculating the open quantum dynamics for driven quantum systems interacting with highly structured bosonic baths by combining the tree tensor network (TTN) decomposition scheme with the bexcitonic generalization of the numerically exact hierarchical equations of motion (HEOM). The method yields a series of quantum master equations for all core tensors in the TTN that efficiently and accurately capture the open quantum dynamics for non-Markovian environments to all orders in the system–bath interaction. These master equations are constructed based on the time-dependent Dirac–Frenkel variational principle, which isolates the optimal dynamics for the core tensors given the TTN ansatz. The dynamics converges to the HEOM when increasing the rank of the core tensors, a limit in which the TTN ansatz becomes exact. We introduce TENSO, tensor equations for non-Markovian structured open systems, as a general-purpose Python code to propagate the TTN-HEOM dynamics. We implement three general propagators for the coupled master equations: two fixed-rank methods that require a constant memory footprint during the dynamics and one adaptive-rank method with a variable memory footprint controlled by the target level of computational error. We exemplify the utility of these methods by simulating a two-level system coupled to a structured bath containing one Drude–Lorentz component and eight Brownian oscillators, which is beyond what can presently be computed using the standard HEOM. Our results show that the TTN-HEOM is capable of simulating both dephasing and relaxation dynamics of driven quantum systems interacting with structured baths, even those of chemical complexity, with an affordable computational cost.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Elucidating Quintet-State Dynamics in Singlet Fission Oligomers and Polymers with Tetracene Pendants

To unlock the potential of molecular engineering for practical quantum sensing and computing, it is essential to create and control pure magnetic states in molecular systems. Singlet fission (SF) in organic materials offers a promising approach by generating pairs of triplet excited states from photoexcited singlets. Here, in this work, we investigate SF in a polymer with strategically positioned tetracene pendant groups along a polynorbornene backbone and its oligomeric counterparts, facilitating intrapolymer through-space coupling. Using continuous-wave and pulsed time-resolved electron paramagnetic resonance (EPR) spectroscopy, we elucidate the spin dynamics and identify key intermediates, including the quintet state, that emerge during SF. Our findings reveal that exciton translational motion along the pendant groups enhances the dissociation of triplet pairs, with oligomer length playing a critical role in modulating spin state interconversion and exciton transport. Our results provide key insights into the SF mechanism in polymeric materials and highlight the role of oligomer length in modulating spin state interconversion and exciton transport. This work advances our understanding of SF in polymers, paving the way for their application in quantum information science and energy conversion technologies.

Bindra, Jasleen K. [Argonne National Laboratory (A↗

Nanosecond solvation dynamics in a polymer electrolyte for lithium batteries

Solvation dynamics critically affect charge transport. Spectroscopic experiments and computer simulations show that these dynamics in aqueous systems occur on a picosecond timescale. In the case of organic electrolytes, however, conflicting values ranging from 1 to several 100 picoseconds have been reported. We resolve this conflict by studying mixtures of an organic polymer and a lithium salt. Lithium ions coordinate with multiple polymer chains, resulting in temporary crosslinks. Relaxation of these crosslinks, detected by quasielastic neutron scattering, are directly related to solvation dynamics. Simulations reveal a broad spectrum of relaxation times. The average timescale for solvation dynamics in both experiment and simulation is one nanosecond. Here we present the direct measurement of ultraslow dynamics of solvation shell break-up in an electrolyte.

25 ENERGY STORAGE↗

Hydropower Scheduling Toolchains: Comparing Experiences in Brazil, Norway, and USA and Implications for Synergistic Research

While hydropower scheduling is a well-defined problem, there are institutional differences that need to be identified to promote constructive and synergistic research. We study how established toolchains of computer models are organized to assist operational hydropower scheduling in Brazil, Norway, and the United States’ Colorado River System (CRS). These three systems have vast hydropower resources, with numerous, geographically widespread, and complex reservoir systems. Although the underlying objective of hydropower scheduling is essentially the same, the systems are operated in different market contexts and with different alternative uses of water, where the stakeholders’ objectives clearly differ. This in turn leads to different approaches when it comes to the scope, organization, and use of models for operational hydropower scheduling and the information flow between the models. Here, we describe these hydropower scheduling toolchains, identify the similarities and differences, and shed light on the original ideas that motivated their creation. We then discuss the need to improve and extend the current toolchains and the opportunities to synergistic research that embrace those contextual differences.

13 HYDRO ENERGY↗

Evaluation of HAL/S language compilability using SAMSO's Compiler Writing System (CWS)

NASA/Langley is engaged in a program to develop an adaptable guidance and control software concept for spacecraft such as shuttle-launched payloads. It is envisioned that this flight software be written in a higher-order language, such as HAL/S, to facilitate changes or additions. To make this adaptable software transferable to various onboard computers, a compiler writing system capability is necessary. A joint program with the Air Force Space and Missile Systems Organization was initiated to determine if the Compiler Writing System (CWS) owned by the Air Force could be utilized for this purpose. The present study explores the feasibility of including the HAL/S language constructs in CWS and the effort required to implement these constructs. This will determine the compilability of HAL/S using CWS and permit NASA/Langley to identify the HAL/S constructs desired for their applications. The study consisted of comparing the implementation of the Space Programming Language using CWS with the requirements for the implementation of HAL/S. It is the conclusion of the study that CWS already contains many of the language features of HAL/S and that it can be expanded for compiling part or all of HAL/S. It is assumed that persons reading and evaluating this report have a basic familiarity with (1) the principles of compiler construction and operation, and (2) the logical structure and applications characteristics of HAL/S and SPL.

Feliciano, M.↗

A programing system for research and applications in structural optimization

The flexibility necessary for such diverse utilizations is achieved by combining, in a modular manner, a state-of-the-art optimization program, a production level structural analysis program, and user supplied and problem dependent interface programs. Standard utility capabilities in modern computer operating systems are used to integrate these programs. This approach results in flexibility of the optimization procedure organization and versatility in the formulation of constraints and design variables. Features shown in numerical examples include: variability of structural layout and overall shape geometry, static strength and stiffness constraints, local buckling failure, and vibration constraints.

Sobieszczanski-Sobieski, J.↗

A programing system for research and applications in structural optimization

The paper describes a computer programming system designed to be used for methodology research as well as applications in structural optimization. The flexibility necessary for such diverse utilizations is achieved by combining, in a modular manner, a state-of-the-art optimization program, a production level structural analysis program, and user supplied and problem dependent interface programs. Standard utility capabilities existing in modern computer operating systems are used to integrate these programs. This approach results in flexibility of the optimization procedure organization and versatility in the formulation of contraints and design variables. Features shown in numerical examples include: (1) variability of structural layout and overall shape geometry, (2) static strength and stiffness constraints, (3) local buckling failure, and (4) vibration constraints. The paper concludes with a review of the further development trends of this programing system.

Sobieszczanski-Sobieski, J.↗

Computer-assisted design of organic synthesis

The computer programs to design synthetic pathways of organic compounds have been utilized throughout the world since the first system was reported by Corey in 1969, and the LHASA was reported in1972 to become the predominant system. Many programs have been reported mainly in the United States and Europe, and groups of corporations, especially chemical companies, have been trying to improve programs and increase the efficiency of research. In Japan, unfortunately, no concrete movement in this area has been seen. Of course, it goes without saying that these kinds of programs are effective for efficient research, but the remarkable aspect is that these can present unexpected data to the researchers to stimulate them to develop new ideas.

Kaminaka, H.↗

Technologies and Designs for Electronic Nanocomputers

Diverse space-related applications have been proposed for microscopic and sub-microscopic structures, mechanisms, and 'organisms'. To govern their functions, many of these tiny systems will require even smaller, nanometer-scale programmable computers, i.e. 'nanocomputers' on-board. This paper provides an overview of the results of a nearly two-year study of the technologies and designs that presently are in development for electronic nanocomputers. Strengths and weaknesses of the various technologies and designs are discussed, as well as promising directions for remedying some of the present research issues in this area. The presentation is a synopsis of a longer MITRE review article on the same subject.

Montemerlo, Michael S.↗

Vestibular plasticity following orbital spaceflight: recovery from postflight postural instability

Results of previous studies suggested that the vestibular mediated postural instability observed in astronauts upon return to earth from orbital spaceflight may be exacerbated by an increased weighting of visual inputs for spatial orientation and control of movement. This study was performed to better understand the roles of visual and somatosensory contributions to recovery of normal sensori-motor postural control in returning astronauts. Preflight and postflight, 23 astronaut volunteers were presented randomly with three trials of six sensory organization test (SOT) conditions in the EquiTest system test battery. Sagittal plane center-of-gravity (COG) excursions computed from ground reaction forces were significantly higher on landing day than preflight for those test conditions presenting sway-referenced visual and/or somatosensory orientation cues. The ratio of summed peak-to-peak COG sway amplitudes on the two sway-referenced vision tests (SOTs 3 + 6) compared to the two eyes closed tests (SOTs 2 + 5) was increased on landing day, indicating an increased reliance on visual orientation cues for postural control. The ratio of peak-to-peak COG excursions on sway-referenced surfaces (SOTs 4, 5 & 6) to an earth fixed support surfaces (SOTs 1, 2 & 3) increased even more after landing suggesting primary reliance on somatosensory orientation cues for recovery of postflight postural stability. Readaptation to sway-referenced support surfaces took longer than readaptation to sway-referenced vision. The increased reliance on visual and somatosensory inputs disappeared in all astronauts 4-8 days following return to earth.

NASA Program Space Physiology and Countermeasures↗

Forming Aggregations using Virtual Sharding: Lessons Learned from Simple Scalable Storage (S3)

Data aggregation is the ability to combine separate datasets to form a single new logical dataset provides users with a powerful abstraction. The advantage of an aggregate dataset is that the users are freed from having to understand, and incorporate into their workflow, knowledge about the (ad hoc) organization of the constituent datasets. However, aggregating large numbers of files can be computationally complex with data server systems performing many repetitive operations. As part of the authors work on subsetting data stored on Amazon Web Service (AWS) Simple Storage Service (S3), we developed technology to read portions of otherwise monolithic data files. This enables the formation of virtual shards for user in subsetting data stored in HDF5 (hierarchical data format, version 5) files. This same tool can be used to form aggregations that combine data stored in many HDF5 files when those files are stored on S3. The nature of the virtual sharding and the algorithm that exploits it for subsetting is such that it can also be used for aggregation with the need for many of the repetitive operations required by the per file aggregation techniques. We will present timing information that demonstrates the flexibility of this approach. However, the lessons learned is that while this is a useful result in and of itself, these very same techniques can be applied in other contexts where data are stored in services and on media other than S3. For example, this same technique can be applied to data stored on spinning disk. Pushing the envelope for S3 forced a reexamination of our data access techniques which lead to unexpected positive benefits.

Gallagher, James↗

Genomes to Structure and Function Workshop Report 2022

The goal of the U.S. Department of Energy (DOE) Biological and Environmental Research (BER) Program is to achieve a predictive understanding of complex biological, earth, and environmental systems with the aim of advancing the nation’s energy and infrastructure security. (https://www.energy.gov/science/ ber/biological-and-environmental-research). To pursue this goal, collaborations among experts in diverse research areas that lead to multidisciplinary projects are indispensable. The roles of DOE’s User Facilities, which offer unique and powerful resources for such research projects, are evolving, and expectations for the facilities are increasing. To respond to Users’ needs, the Joint Genome Institute (JGI) and Environmental Molecular Sciences Laboratory (EMSL) initiated the Facilities Integrating Collaborations for User Science (FICUS) program in 2014. This collaboration has grown into a popular and successful program, advancing more than 100 multidisciplinary projects to date. Similarly, the new interFacility collaborations among the JGI, EMSL, and User resources for BER structural biology and imaging at the Basic Energy Science (BES) Program’s synchrotron and neutron facilities are becoming essential for cutting-edge transdisciplinary science. To further explore the need for the BER research community to combine genomic, functional, and structural approaches to advance their research, an organizing committee was formed to develop and jointly host a 3-part workshop. The committee’s members represented seven DOE National Laboratory User Facilities (Appendix 1 lists the members). The “Genomes to Structure and Function” virtual workshop (see Appendices 2–5) was composed of three sessions. The first session, titled “Molecular Structures” (October 27– 28, 2021), highlighted diverse integrative experimental and computational approaches correlating structural data with sequencing and functional information, as well as predicting protein structures to model complex biological systems. The second session, “Intracellular Organization, and Material Synthesis and Decomposition” (December 15–16, 2021), covered imaging methods for observing, quantifying, and manipulating biosystems. The third session, “Imaging the Rhizosphere and Cellular Organization” (January 26–27, 2022) emphasized advanced and non-invasive imaging techniques applied to plant root-microbe-soil interactions.

59 BASIC BIOLOGICAL SCIENCES↗

RAMIS DBMS Update

Highlights of a round table discussion of end-user computing, IBM strategies, fourth generation languages, and directions for software innovation are presented as well as observations from an in-depth study of 271 organizations. The RAMIS data base management system is evaluated according to 10 defining criteria for a fourth-generation language: result-oriented programming; common language/demand level adaptability; application extension; user/machine insulation; work station environment; comprehensive software toolkit; integrating perspective on computing and data resources; end user data base capability; accessible dictionaries; and user assistance/facility coordination.

Head, J.↗

A review of machine learning in building load prediction

The surge of machine learning in recent years has been empowering engineer modeling in various fields. The decreasing hardware cost, increasing data accessibility, and advances of building automation system (BAS) allow the collection and storage of a significant amount of building operation data. The two facts provide great opportunities of applying machine learning to building energy systems modeling and analysis. There are a great number of research papers on this topic but there lacks a comprehensive and general review to summarize the current development, limitations, gaps and future trend. In this review paper series, machine learning techniques in building energy system modeling and analysis are reviewed under the organization and logic of the machine learning definition by Tom M. Mitchell: a computer program is said to learn from experience E with respect to some class of tasks T and performance measure P if its performance at tasks in T, as measured by P, improves with experience E. This paper is the first part of the review paper series, which focuses on building load prediction. First, the applications of building load prediction model (task T) are reviewed. Then, the modeling algorithms improving machine learning performance and accuracy (performance P) are reviewed. At the same time, the literature on the data perspective for modeling (experience E), including data engineering from sensors level to data level, pre-processing, feature extraction and selection, is reviewed. Finally, what is well-studied and what is lacking but with great potential are concluded; the gaps between present and future utilization of machine learning techniques are identified; the future trend and development are also predicted. The target readers of this paper are not only researchers from the building side who can get exposed to cutting edge machine learning tools, but also those from machine learning side who can understand the potential and challenge to apply machine learning in buildings.

Liang, Zhang↗

Robust, Accurate, and Efficient: Quantum Embedding Using the Huzinaga Level-Shift Projection Operator for Complex Systems

Using wave function (WF) in density functional theory (DFT) embedding methods provides a framework for performing localized, high-accuracy WF calculations on a system, while not incurring the full computational cost of the WF calculation on the full system. To effectively partition a system into localized WF and DFT subsystems, we utilize the Huzinaga level-shift projection operator within an absolutely localized basis. In this work, we study the ability of the absolutely localized Huzinaga level-shift projection operator method to study complex WF and DFT partitions, including partitions between multiple covalent bonds, a double bond, and transition-metal–ligand bonds. We find that our methodology can accurately describe all of these complex partitions. Additionally, we study the robustness of this method with respect to the WF method, specifically where the embedded systems were described using a multiconfigurational WF method. We found that the method is systematically improvable with respect to both the number of atoms in the WF region and the size of the basis set used, with energy errors less than 1 kcal/mol. Additionally, we calculated the adsorption energy of H2 to a model of an iron metal–organic framework (Fe-MOF-74) to within 1 kcal/mol compared to CASPT2 calculations performed on the full model while incurring only a small fraction of the full computational cost. In conclusion, this work demonstrates that the absolutely localized Huzinaga level-shift projection operator method is applicable to very complex systems with difficult electronic structures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗