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At least 883 records · Page 49

All sources NASA NTRS DOE OSTI

DOE OSTI2021

Variational Quantum Chemistry Programs in JaqalPaq

We present example quantum chemistry programs written with JaqalPaq, a python meta-programming language used to code in Jaqal (Just Another Quantum Assembly Language). These JaqalPaq algorithms are intended to be run on the Quantum Scientific Computing Open User Testbed (QSCOUT) platform at Sandia National Laboratories. Our exemplars use the variational quantum eigensolver (VQE) quantum algorithm to compute the ground state energies of the H2, HeH+, and LiH molecules. Since the exemplars focus on how to program in JaqalPaq, the calculations of the second-quantized Hamiltonians are performed with the PySCF python package, and the mappings of the fermions to qubits are obtained from the OpenFermion python package. Using the emulator functionality of JaqalPaq, we emulate how these exemplars would be executed on an error-free QSCOUT platform and compare the emulated computation of the bond-dissociation curves for these molecules with their exact forms within the relevant basis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

StructuredFuzzer: Fuzzing Structured Text-Based Control Logic Applications

Rigorous testing methods are essential for ensuring the security and reliability of industrial controller software. Fuzzing, a technique that automatically discovers software bugs, has also proven effective in finding software vulnerabilities. Unsurprisingly, fuzzing has been applied to a wide range of platforms, including programmable logic controllers (PLCs). However, current approaches, such as coverage-guided evolutionary fuzzing implemented in the popular fuzzer American Fuzzy Lop Plus Plus (AFL++), are often inadequate for finding logical errors and bugs in PLC control logic applications. They primarily target generic programming languages like C/C++, Java, and Python, and do not consider the unique characteristics and behaviors of PLCs, which are often programmed using specialized programming languages like Structured Text (ST). Furthermore, these fuzzers are ill suited to deal with complex input structures encapsulated in ST, as they are not specifically designed to generate appropriate input sequences. This renders the application of traditional fuzzing techniques less efficient on these platforms. To address this issue, this paper presents a fuzzing framework designed explicitly for PLC software to discover logic bugs in applications written in ST specified by the IEC 61131-3 standard. The proposed framework incorporates a custom-tailored PLC runtime and a fuzzer designed for the purpose. We demonstrate its effectiveness by fuzzing a collection of ST programs that were crafted for evaluation purposes. We compare the performance against a popular fuzzer, namely, AFL++. The proposed fuzzing framework demonstrated its capabilities in our experiments, successfully detecting logic bugs in the tested PLC control logic applications written in ST. On average, it was at least 83 times faster than AFL++, and in certain cases, for example, it was more than 23,000 times faster.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Machine Reading at Scale: A Search Engine for Scientific and Academic Research

The Internet, much like our universe, is ever-expanding. Information, in the most varied formats, is continuously added to the point of information overload. Consequently, the ability to navigate this ocean of data is crucial in our day-to-day lives, with familiar tools such as search engines carving a path through this unknown. In the research world, articles on a myriad of topics with distinct complexity levels are published daily, requiring specialized tools to facilitate the access and assessment of the information within. Recent endeavors in artificial intelligence, and in natural language processing in particular, can be seen as potential solutions for breaking information overload and provide enhanced search mechanisms by means of advanced algorithms. As the advent of transformer-based language models contributed to a more comprehensive analysis of both text-encoded intents and true document semantic meaning, there is simultaneously a need for additional computational resources. Information retrieval methods can act as low-complexity, yet reliable, filters to feed heavier algorithms, thus reducing computational requirements substantially. In this work, a new search engine is proposed, addressing machine reading at scale in the context of scientific and academic research. It combines state-of-the-art algorithms for information retrieval and reading comprehension tasks to extract meaningful answers from a corpus of scientific documents. The solution is then tested on two current and relevant topics, cybersecurity and energy, proving that the system is able to perform under distinct knowledge domains while achieving competent performance.

Sousa, Norberto (ORCID:0000000329194817)↗

DOE OSTI2025

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics

Large language models have revolutionized artificial intelligence by enabling large, generalizable models trained through self-supervision. This paradigm has inspired the development of scientific foundation models (FMs). However, applying this capability to experimental particle physics is challenging due to the sparse, spatially distributed nature of detector data, which differs dramatically from natural language. This work addresses if an FM for particle physics can scale and generalize across diverse tasks. We introduce a new dataset with more than 11 million particle collision events and a suite of downstream tasks and labeled data for evaluation. We propose a novel self-supervised training method for detector data and demonstrate its neural scalability with models that feature up to 188 million parameters. With frozen weights and task-specific adapters, this FM consistently outperforms baseline models across all downstream tasks. The performance also exhibits robust data-efficient adaptation. Further analysis reveals that the representations extracted by the FM are task-agnostic but can be specialized via a single linear mapping for different downstream tasks.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Pathways to IEC Standards for Heliostat Design Qualification and Site Acceptance in Central Receiver CSP Applications

This paper surveys the existing landscape of standards relevant to heliostats, identifies their gaps, and proposes a path forward to a comprehensive set of heliostat guidelines, technical specifications, and standards under the framework of International Electrotechnical Commission (IEC) TC 117. Gaps in existing guidelines and standards are surveyed using a three-tiered taxonomy: component-level, heliostat-level, and field-level. At each level, the gap analysis is followed by a proposal for a coordinated path forward on the development of standards. At the component level, advances in the understanding of wind loading should inform a technical specification for drives and structures. Reflectors require consolidation of measurement guidelines into existing standards documents. Communications & controls require technical standards to inform their selection and secure implementation. At the heliostat level, IEC 62817 (solar trackers) adequately characterizes drive systems, structures, and electronics, but requires adaptation to heliostats' use patterns, operating modes, and expected life cycles. IEC 62817 does not address heliostat beam quality and pointing accuracy, but the process for determining both is elaborated in the SolarPACES Guideline for Heliostat Performance Testing. This SolarPACES document requires two main modifications: adaptation to IEC language and inclusion of testing after heliostats which have undergone accelerated weathering and mechanical cycling (to understand performance degradation). At the field level, IEC 62862-4-2 addresses the function and control of heliostat fields but does not cover the statistically rigorous testing of heliostat groups, or field performance factors like security and soiling. The addition of documents under IEC-62862-4 is proposed to address this gap.

beam↗

DOE OSTI2020

Developing a sustainability science approach for water systems

We convened a workshop to enable scientists who study water systems from both social science and physical science perspectives to develop a shared language. This shared language is necessary to bridge a divide between these disciplines’ different conceptual frameworks. As a result of this workshop, we argue that we should view socio-hydrological systems as structurally co-constituted of social, engineered, and natural elements and study the “characteristic management challenges” that emerge from this structure and reoccur across time, space, and socioeconomic contexts. This approach is in contrast to theories that view these systems as separately conceptualized natural and social domains connected by bi-directional feedbacks, as is prevalent in much of the water systems research arising from the physical sciences. A focus on emergent characteristic management challenges encourages us to go beyond searching for evidence of feedbacks and instead ask questions such as: What types of innovations have successfully been used to address these challenges? What structural components of the system affect its resilience to hydrological events and through what mechanisms? Are there differences between successful and unsuccessful strategies to solve one of the characteristic management challenges? If so, how are these differences affected by institutional structure and ecological and economic contexts? To answer these questions, social processes must now take center stage in the study and practice of water management. We also argue that water systems are an important class of coupled systems with relevance for sustainability science because they are particularly amenable to the kinds of systematic comparisons that allow knowledge to accumulate. Indeed, the characteristic management challenges we identify are few in number and recur over most of human history and in most geographical locations. This recurrence should allow us to accumulate knowledge to answer the above questions by studying the long historical record of institutional innovations to manage water systems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Projected Urban Morphology of the Los Angeles Area by the Year 2100

This dataset provides projections of urban building morphologies for the Los Angeles urban area at 30-meter spatial resolution. It contains 192 raster files that detail two primary building attributes: building footprint fractions (ranging from 0 to 1) and average building heights (ranging from 0 to 75 meters). The projections account for a wide range of future pathways, covering two Shared Socioeconomic Pathway (SSP) scenarios (SSP3 and SSP5), two population scenarios, two developed land intensification scenarios, and four distinct levels of intensification. The dataset was created using dual Generative Adversarial Networks (GANs) trained on 2015 land cover and building properties from the National Land Cover Database (NLCD) and Model America datasets. Supporting information on the dataset has been described in the LAUrbanAreaMorphologyProjections2100_README.txt file.

Pandey, Bhartendu↗

DOE OSTI2025

MSD CoP Webinar: "Generative agents: A new frontier for representing human actors and their behavior in MSD models"

Context: This webinar was hosted by the MultiSector Dynamics Community of Practice (MSD CoP; https://multisectordynamics.org). Talk #1: Behavioral Generative Agents for Energy Operations Presenter: Dr. Cong Chen (Thayer School of Engineering, Dartmouth College) Abstract: Accurately modeling consumer behavior in energy operations remains challenging due to inherent uncertainties, behavioral complexities, and limited empirical data. This talk introduces a novel approach leveraging generative agents--artificial agents powered by large language models--to realistically simulate customer decision-making in dynamic energy operations. Talk #2: Simulating multiple human perspectives in socio-ecological systems using large language models Presenter: Dr. Yongchao Zeng (Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU) of the Karlsruhe Institute of Technology in Germany) Abstract: Understanding socio-ecological systems requires insights from diverse stakeholder perspectives. This talk describes a novel simulation system called HoPeS (Human-oriented Perspective Shifting). HoPeS enables model users to not only explore simulated socio-ecological systems (SESs) from a third-person observer's perspective but also take any of the simulated stakeholder roles, like playing an RPG game. By shifting multiple perspectives, model users can reflect and integrate the situated knowledge learned through the participatory simulation, approximating a more holistic and less biased understanding of SESs. Moderators: Jim Yoon (MSD CoP Human Systems Modeling Working Group Co-Chair); Stefano Galelli (MSD CoP Using AI to Enhance MSD Research Working Group Co-Chair); Patrick M. Reed (MSD CoP Facilitation Team) This webinar was held on: November 13th, 2025 from 12-1 PM EST.

Artificial Intelligence↗

DOE OSTI2020

Problems of Nuclear Technology and Radiation Safety

This work discusses ethical issues arising in the course of the development of nuclear technologies and related issues of radiation safety. Attention is paid to ethical dilemmas and proposed solutions. The author suggests a critical analysis of the relevant discussions, conducted, first of all, in the English-language literature, and muses on the specifics associated with their transfer to the Russian context. This study considers ethical problems arising in context of the depletion of uranium resources and nuclear waste management and including the inevitable risks for the present and future generations, such as inter- and intragenerational justice (Gardiner's problem) and the problem of the identity of future generations (Parfit’s problem); problems of collectivity and individuality in the assessment of permissible radiation doses for workers at nuclear enterprises and the population associated with the need to combine deontological and utilitarian approaches in the practice of radiation protection. The author demonstrates cultural differences in attitudes towards the safety of the current and future generations of the population of countries and regions and the associated ambiguities in the choice of technology for nuclear reactors, long-term disposal or processing of nuclear waste; double standards in ensuring the radiation safety of personnel of nuclear facilities and the population; ethical problems of risk compensation to workers of radiation-hazardous production facilities; issues of gender differences in sensitivity to radiation exposure, gender equality and discrimination in relation to access to the labor market in the nuclear industry. The article elucidates the importance of socio-humanitarian discussion of the ethical problems of nuclear technologies and radiation safety Such debates currently are almost absent in the Russian-language philosophical literature, despite its exceptional importance due to both the level of development of nuclear energy in Russia and the potential risks that these technologies pose to current and future generations of both employees of nuclear facilities and the population of the country, neighboring countries, and the world. The purpose of this article, thus, is to initiate such a discussion.

ethics of science and technology↗

DOE OSTI2024

Innovating the next generation of commercial smart building software

Nearly 30% of commercial building energy use is wasted due to equipment faults and HVAC controls problems. The result is increased emissions, compromised comfort and productivity, and less reliable coordination of building power needs with a clean grid. The energy impact alone represents $17 billion in potential savings. Today’s smart building software provides a robust solution to address these operational deficiencies. Energy management and information systems (EMIS) are saving up to 9% on average, with two-year paybacks. They are being incorporated into energy management processes, commissioning services, and utility programs. As effective as they are, two barriers prevent even deeper benefits; limited personnel to fix problems once they are identified, and the expense and time to manually implement changes in control systems. In partnership with the research community, the EMIS industry is developing new capabilities to overcome these barriers. Moving beyond siloed products for either fault detection and diagnostics, or optimal control, these new capabilities empower users to not only automatically identify faults, but also to push corrective action, and control improvements to their buildings. In this paper, several areas for enhancements are documented: ‘one-time’ correction of faults such as setpoints, schedules, and economizer lockouts; short-term active testing for automated proportional integral derivative (PID) loop tuning and functional testing; and continuous supervisory control for demand flexibility and year-round efficiency. Results are presented from a pair of partner implementations out of a dozen providers integrating these enhancements into their products, including field tests from across the country, and insights into operator acceptance and integration into operations and maintenance practices.

Casillas, Armando↗

DOE OSTI2011

Data analysis using the Gnu R system for statistical computation

R is a language system for statistical computation. It is widely used in statistics, bioinformatics, machine learning, data mining, quantitative finance, and the analysis of clinical drug trials. Among the advantages of R are: it has become the standard language for developing statistical techniques, it is being actively developed by a large and growing global user community, it is open source software, it is highly portable (Linux, OS-X and Windows), it has a built-in documentation system, it produces high quality graphics and it is easily extensible with over four thousand extension library packages available covering statistics and applications. This report gives a very brief introduction to R with some examples using lattice QCD simulation results. It then discusses the development of R packages designed for chi-square minimization fits for lattice n-pt correlation functions.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2010

Exploiting first-class arrays in Fortran for accelerator programming

Emerging architectures for high performance computing often are well suited to a data parallel programming model. This paper presents a simple programming methodology based on existing languages and compiler tools that allows programmers to take advantage of these systems. We will work with the array features of Fortran 90 to show how this infrequently exploited, standardized language feature is easily transformed to lower level accelerator code. Our transformations are based on a mapping from Fortran 90 to C++ code with OpenCL extensions. The sheer complexity of programming for clusters of many or multi-core processors with tens of millions threads of execution make the simplicity of the data parallel model attractive. Furthermore, the increasing complexity of todays applications (especially when convolved with the increasing complexity of the hardware) and the need for portability across hardware architectures make a higher-level and simpler programming model like data parallel attractive. The goal of this work has been to exploit source-to-source transformations that allow programmers to develop and maintain programs at a high-level of abstraction, without coding to a specific hardware architecture. Furthermore these transformations allow multiple hardware architectures to be targeted without changing the high-level source. It also removes the necessity for application programmers to understand details of the accelerator architecture or to know OpenCL.

43 PARTICLE ACCELERATORS↗

DOE OSTI2014

COMPOSE-HPC: Software Composition for Extreme Scale Computational Science and Engineering

Software composition is an important aspect of computational science software engineering due to large scale production science codes involving multiple programming languages, execution and concurrency models. To date, programmers must manage the complexity of building and maintaining such systems largely by hand with minimal (if any) automated assistance. As such, a great deal of programmer time is spent generating and maintaining code which leads to a high maintenance and development cost, as well as an increased risk of errors being introduced by hand than would be expected in an automated system. COMPOSE-HPC was a multi-institutional effort, with the Galois contribution focused on a specific area of code analysis and software infrastructure. Specifically, Galois led the design and implementation for the Parser for Annotations in a User-specified Language (PAUL), as well as collaborating with SNL and LLNL on the Retargetable Open Transformation Engine (ROTE). Both components were built on top of the ROSE compiler infrastructure from LLNL. All artifacts developed under the COMPOSE-HPC program are available on the github.com and sourceforge.net open source hosting sites under permissive BSD3 software licenses.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2014

A Runtime Verification Framework for Control System Simulation

n a standard workflow for the validation of a control system, the control system is implemented as an extension to a simulator. Such simulators are complex software systems, and engineers may unknowingly violate constraints a simulator places on extensions. As such, errors may be introduced in the implementation of either the control system or the simulator leading to invalid simulation results. This paper presents a novel runtime verification approach for verifying control system implementations within simulators. The major contribution of the approach is the two-tier specification process. In the first tier, engineers model constraints using a domain-specific language tailored to modeling a controller’s response to changes in its input. The language is high-level and effectively hides the implementation details of the simulator, allowing engineers to specify design-level constraints independent of low-level simulator interfaces. In the second tier, simulator developers provide mapping rules for mapping design-level constraints to the implementation of the simulator. Using the rules, an automated tool transforms the design-level specifications into simulator-specific runtime verification specifications and generates monitoring code which is injected into the implementation of the simulator. During simulation, these monitors observe the input and output variables of the control system and report changes to the verifier. The verifier checks whether these changes follow the constraints of the control system. We describe application of this approach to the verification of the constraints of an HVAC control system implemented with the power grid simulator GridLAB-D.

control system↗

DOE OSTI2014

An Ontology Design Pattern for Surface Water Features

Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities can be found due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology. It can then be used to systematically incor-porate concepts that are specific to a culture, language, or scientific domain. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex surface water ontologies. A fundamental distinction is made in this on-tology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is imple-mented in OWL, but Description Logic axioms and a detailed explanation is provided. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. A discussion about why there is a need to complement the pattern with other ontologies, es-pecially the previously developed Surface Network pattern is also provided. Fi-nally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through a few queries and annotated geospatial datasets.

GIS↗

DOE OSTI2015

End-to-end interoperability and workflows from building architecture design to one or more simulations

An end-to-end interoperability and workflows from building architecture design to one or more simulations, in one aspect, may comprise establishing a BIM enablement platform architecture. A data model defines data entities and entity relationships for enabling the interoperability and workflows. A data definition language may be implemented that defines and creates a table schema of a database associated with the data model. Data management services and/or application programming interfaces may be implemented for interacting with the data model. Web services may also be provided for interacting with the data model via the Web. A user interface may be implemented that communicates with users and uses the BIM enablement platform architecture, the data model, the data definition language, data management services and application programming interfaces to provide functions to the users to perform work related to building information management.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

End-to-end interoperability and workflows from building architecture design to one or more simulations

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2015

The Particle Accelerator Simulation Code PyORBIT

The particle accelerator simulation code PyORBIT is presented. The structure, implementation, history, parallel and simulation capabilities, and future development of the code are discussed. The PyORBIT code is a new implementation and extension of algorithms of the original ORBIT code that was developed for the Spallation Neutron Source accelerator at the Oak Ridge National Laboratory. The PyORBIT code has a two level structure. The upper level uses the Python programming language to control the flow of intensive calculations performed by the lower level code implemented in the C++ language. The parallel capabilities are based on MPI communications. The PyORBIT is an open source code accessible to the public through the Google Open Source Projects Hosting service.

Accelerator Simulation↗