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DOE OSTI2024

Forte: A suite of advanced multireference quantum chemistry methods

Software development plays a critical role in advancing quantum chemistry, enabling the exploration of new fundamental theoretical ideas and modeling systems of ever-increasing complexity. In the past decade, the availability of quantum chemistry packages that use modular designs and provide application programming interfaces (APIs) has enabled the creation of specialized software plugins, enhancing the capabilities of the original codes. Here, the availability of well-documented APIs is particularly beneficial in the context of academic scientific software development because it reduces the entry barrier for new developers and shields them from the complexities of large software projects.

74 ATOMIC AND MOLECULAR PHYSICS↗

DOE OSTI2017

Long-Term Fish Monitoring in Large Rivers: Utility of “Benchmarking” across Basins

Abstract In business, benchmarking is a widely used practice of comparing your own business processes to those of other comparable companies and incorporating identified best practices to improve performance. Biologists and resource managers designing and conducting monitoring programs for fish in large river systems tend to focus on single river basins or segments of large rivers, missing opportunities to learn from those conducting fish monitoring in other rivers. We briefly examine five long-term fish monitoring programs in large rivers in the United States (Colorado, Columbia, Mississippi, Illinois, and Tallapoosa rivers) and identify opportunities for learning across programs by detailing best monitoring practices and why these practices were chosen. Although monitoring objectives, methods, and program maturity differ between each river system, examples from these five case studies illustrate the important role that long-term monitoring programs play in interpreting temporal and spatial shifts in fish populations for both established objectives and newly emerging questions. We suggest that deliberate efforts to develop a broader collaborative network through benchmarking will facilitate sharing of ideas and development of more effective monitoring programs.

Ward, David L.↗

DOE OSTI2017

Expressing Parallelism with ROOT

The need for processing the ever-increasing amount of data generated by the LHC experiments in a more efficient way has motivated ROOT to further develop its support for parallelism. Such support is being tackled both for shared-memory and distributed-memory environments. The incarnations of the aforementioned parallelism are multi-threading, multi-processing and cluster-wide executions. In the area of multi-threading, we discuss the new implicit parallelism and related interfaces, as well as the new building blocks to safely operate with ROOT objects in a multi-threaded environment. Regarding multi-processing, we review the new MultiProc framework, comparing it with similar tools (e.g. multiprocessing module in Python). Finally, as an alternative to PROOF for cluster-wide executions, we introduce the efforts on integrating ROOT with state-of-the-art distributed data processing technologies like Spark, both in terms of programming model and runtime design (with EOS as one of the main components). For all the levels of parallelism, we discuss, based on real-life examples and measurements, how our proposals can increase the productivity of scientists.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2011

iMOSFLM: a new graphical interface for diffraction-image processing with MOSFLM

A new graphical user interface to the MOSFLM program has been developed to simplify the processing of macromolecular diffraction data. The interface, iMOSFLM, allows data processing via a series of clearly defined tasks and provides visual feedback on the progress of each stage. iMOSFLM is a graphical user interface to the diffraction data-integration program MOSFLM. It is designed to simplify data processing by dividing the process into a series of steps, which are normally carried out sequentially. Each step has its own display pane, allowing control over parameters that influence that step and providing graphical feedback to the user. Suitable values for integration parameters are set automatically, but additional menus provide a detailed level of control for experienced users. The image display and the interfaces to the different tasks (indexing, strategy calculation, cell refinement, integration and history) are described. The most important parameters for each step and the best way of assessing success or failure are discussed.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Efficient Hierarchical State Vector Simulation of Quantum Circuits via Acyclic Graph Partitioning

Early but promising results in quantum computing have been enabled by the concurrent development of quantum algorithms, devices, and materials. Classical simulation of quantum programs has enabled the design and analysis of algorithms and implementation strategies targeting current and anticipated quantum device architectures. In this paper, we present a graph-based approach to achieve efficient quantum circuit simulation. Our approach involves partitioning the graph representation of a given quantum circuit into sub-graphs/circuits that exhibit better data locality. Simulation of each sub-circuit is organized hierarchically, with the iterative construction and simulation of smaller state vectors, improving overall performance. Also, this partitioning reduces the number of passes through data, improving the total computation time. We present three partitioning strategies and observe that acyclic graph partitioning typically results in the best time-to-solution. In contrast, other strategies reduce the partitioning time at the expense of potentially increased simulation times. Experimental evaluation demonstrates the effectiveness of our approach.

Fang, Bo↗

DOE OSTI2014

SU-E-J-35: Clinical Performance Evaluation of a Phase II Proton CT Scanner

Purpose: To develop the methodology to evaluate the clinical performance of a Phase II Proton CT scanner Methods: Range errors on the order of 3%-5% constitute a major uncertainty in current charged particle treatment planning based on Hounsfield Unit (HU)-relative stopping power (RSP) calibration curves. Within our proton CT collaboration, we previously developed and built a Phase I proton CT scanner that provided a sensitive area of 9 cm (axial) × 18 cm (in-plane). This scanner served to get initial experience with this new treatment planning tool and to incorporate lessons learned into the next generation design. A Phase II scanner was recently completed and is now undergoing initial performance testing. It will increase the proton acquisition rate and provide a larger detection area of 9 cm x 36 cm. We are now designing a comprehensive evaluation program to test the image quality, imaging dose, and range uncertainty associated with this scanner. The testing will be performed along the lines of AAPM TG 66. Results: In our discussion of the evaluation protocol we identified the following priorities. The image quality of proton CT images, in particular spatial resolution and low-density contrast discrimination, will be evaluated with the Catphan600 phantom. Initial testing showed that the Catphan uniformity phantom did not provide sufficient uniformity; it was thus replaced by a cylindrical water phantom. The imaging dose will be tested with a Catphan dose module, and compared to a typical cone beam CT dose for comparable image quality. Lastly, we developed a dedicated dosimetry range phantom based on the CIRS pediatric head phantom HN715. Conclusion: A formal evaluation of proton CT as a new tool for proton treatment planning is an important task. The availability of the new Phase II proton CT scanner will allow us to perform this task. This research is supported by the National Institute of Biomedical Imaging and Bioengineering of the NIH under award number R01EB013118. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2016

Minimizing treatment planning errors in proton therapy using failure mode and effects analysis

Purpose: Failure mode and effects analysis (FMEA) is a widely used tool to evaluate safety or reliability in conventional photon radiation therapy. However, reports about FMEA application in proton therapy are scarce. The purpose of this study is to apply FMEA in safety improvement of proton treatment planning at their center. Methods: The authors performed an FMEA analysis of their proton therapy treatment planning process using uniform scanning proton beams. The authors identified possible failure modes in various planning processes, including image fusion, contouring, beam arrangement, dose calculation, plan export, documents, billing, and so on. For each error, the authors estimated the frequency of occurrence, the likelihood of being undetected, and the severity of the error if it went undetected and calculated the risk priority number (RPN). The FMEA results were used to design their quality management program. In addition, the authors created a database to track the identified dosimetric errors. Periodically, the authors reevaluated the risk of errors by reviewing the internal error database and improved their quality assurance program as needed. Results: In total, the authors identified over 36 possible treatment planning related failure modes and estimated the associated occurrence, detectability, and severity to calculate the overall risk priority number. Based on the FMEA, the authors implemented various safety improvement procedures into their practice, such as education, peer review, and automatic check tools. The ongoing error tracking database provided realistic data on the frequency of occurrence with which to reevaluate the RPNs for various failure modes. Conclusions: The FMEA technique provides a systematic method for identifying and evaluating potential errors in proton treatment planning before they result in an error in patient dose delivery. The application of FMEA framework and the implementation of an ongoing error tracking system at their clinic have proven to be useful in error reduction in proton treatment planning, thus improving the effectiveness and safety of proton therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

Synthetic genetic circuits as a means of reprogramming plant roots

We report the shape of a plant’s root system influences its ability to reach essential nutrients in the soil and to acquire water during drought. Progress in engineering plant roots to optimize water and nutrient acquisition has been limited by our capacity to design and build genetic programs that alter root growth in a predictable manner. We developed a collection of synthetic transcriptional regulators for plants that can be compiled to create genetic circuits. These circuits control gene expression by performing Boolean logic operations and can be used to predictably alter root structure. This work demonstrates the potential of synthetic genetic circuits to control gene expression across tissues and reprogram plant growth.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Python and HPC for High Energy Physics Data Analyses

High level abstractions in Python that can utilize computing hardware well seem to be an attractive option for writing data reduction and analysis tasks. In this paper, we explore the features available in Python which are useful and efficient for end user analysis in High Energy Physics (HEP). A typical vertical slice of an HEP data analysis is somewhat fragmented: the state of the reduction/analysis process must be saved at certain stages to allow for selective reprocessing of only parts of a generally time-consuming workflow. Also, algorithms tend to to be modular because of the heterogeneous nature of most detectors and the need to analyze different parts of the detector separately before combining the information. This fragmentation causes difficulties for interactive data analysis, and as data sets increase in size and complexity (O10 TiB for a “small” neutrino experiment to the O10 PiB currently held by the CMS experiment at the LHC), data analysis methods traditional to the field must evolve to make optimum use of emerging HPC technologies and platforms. Mainstream big data tools, while suggesting a direction in terms of what can be done if an entire data set can be available across a system and analysed with high-level programming abstractions, are not designed with either scientific computing generally, or modern HPC platform features in particular, such as data caching levels, in mind. Our example HPC use case is a search for a new elementary particle which might explain the phenomenon known as “Dark Matter”. Here, using data from the CMS detector, we will use HDF5 as our input data format, and MPI with Python to implement our use case.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2024

Design and implementation of a verified interpreter for additive manufacturing programs: Experience report

Explore the source record for details and available documents.

Computer science↗

DOE OSTI2019

Joint Optimization Scheme for the Planning and Operations of Shared Autonomous Electric Vehicle Fleets Serving Mobility on Demand

As the transportation sector undergoes three major transformations—electrification, shared/on-demand mobility, and automation—there are new challenges to analyzing the impacts of these trends on both the transportation system and the power sector. Most models that analyze the requirements of fleets of shared autonomous electric vehicles (SAEVs) operate at the scale of an urban region, or smaller. A quadratically constrained, quadratic programming problem is formulated, designed to model the requirements of SAEVs at a national scale. The size of the SAEV fleet, the necessary charging infrastructure, the fleet charging schedule, and the dispatch required to serve demand for trips in a region are treated as decision variables. By minimizing both the amortized cost of the fleet and chargers as well as the operational costs of charging, it is possible to explore the coupled interactions between system design and operation. To apply the model at a national scale, key complications about fleet operations are simplified; but a detailed agent-based regional simulation model to parameterize those simplifications is leveraged. Preliminary results are presented, finding that all mobility in the United States (U.S.) currently served by 276 million personally owned vehicles could be served by 12.5 million SAEVs at a cost of $\$ 0.27$/vehicle-mile or $ 0.18/passenger-mile. In conclusion, the energy requirements for this fleet would be 1142 GWh/day (8.5% of 2017 U.S. electricity demand) and the peak charging load 76.7 GW (11% of U.S. power peak). Several model sensitivities are explored, and it is found that sharing is a key factor in the analysis.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Assessment of Knowledge, Attitudes, and Practices Toward Ticks and Tickborne Disease among Healthcare Professionals Working in Schools in New York and Maryland

Healthcare Professionals Working in Schools (HPWS) are responsible for providing health services to students and play a role in providing education to prevent illnesses, including tickborne diseases (TBD). Providing TBD education to children has been shown to increase prevention behaviors and knowledge of TBD symptoms, but little is known regarding the current state of TBD awareness among HPWS. In spring 2019 we conducted a cross-sectional knowledge, attitudes, and practices (KAP) survey of HPWS in two states with a high incidence of Lyme disease (LD) to inform design of TBD prevention programs. The survey queried general knowledge of TBDs, school practices regarding TBDs, and availability of TBD resources. Overall, higher confidence, experience, risk perception, prior training on TBD, and more years employed as a HPWS were independently associated with knowledge of LD transmission, symptoms, and correct tick removal practices. State and local health departments should consider prioritizing engagement with HPWS to provide educational opportunities about tickborne diseases.

Nursing↗

DOE OSTI2026

Hazard and risk analysis framework for nuclear power plant–based integrated energy systems

Employing integrated energy systems (IESs) with nuclear power plants (NPPs) can improve NPP utilization by leveraging dedicated thermal and electric power delivery, but it may also increase operational safety risks. This paper presents a framework to identify and quantify hazards and risks for such IESs. The framework combines accidentology to review past industrial accidents with failure modes and effects analysis (FMEA) to identify potential future incidents. Hydrogen explosion and toxic chemical release hazards are of particular concern. Explosion consequences are quantified using the Bauwens-Dorofeev (Bauwens) and trinitrotoluene equivalent mass (TNT-EM) methods, while chemical release consequences are computed using the Gaussian atmospheric dispersion method. Operational disturbances from direct electrical and thermal integration that may affect NPP safety are modeled using probabilistic risk analysis (PRA). Hazards and risks are then evaluated for regulatory compliance. The framework is applied to IESs comprising pressurized or boiling water reactors supplying three levels of thermal and electrical power to industrial customers. Case studies include high-temperature steam electrolysis hydrogen plants of varying capacities and a synthetic fuel production plant. Sensitivity analysis examines piping component failures in the PRA model as a precursor to cost estimation for thermal extraction line design. Additionally, Fussel-Vessely (FV) and risk increase importance (RII) measures identify risk-informed design improvements for the thermal extraction system. FMEA highlights hazards such as loss of offsite power, prompt loss of electrical load, loss of thermal output, and immediate steam diversion, in addition to hydrogen explosions and toxic chemical releases. Both Bauwens and TNT-EM methods suggest maintaining several hundred meters of separation between the NPP and hydrogen facility to mitigate explosion risks. PRA results show a maximum initiating event frequency increase of 1.15% and an overall risk increase of 0.28%. Importance measure analysis identifies upstream pipe leak isolation components as critical. Evaluating the results against safety regulations, it is concluded that hazards and risks can be managed to comply with regulations through risk-informed thermal and electrical connection designs, component selection, maintenance programs, and safe separation distances between NPPs and integrated industrial facilities.

08 - HYDROGEN↗

DOE OSTI2011

Microgrid Design, Development and Demonstration - Final Report for Phase I and Phase II

This document constitutes GE’s final report for the Microgrid Design, Development and Demonstration program for DOE’s Office of Electricity Delivery and Energy Reliability, Award DE-FC02-05CH11349. It contains the final report for Phase I in Appendix I, and the results the work performed in Phase II. The program goal was to develop and demonstrate a Microgrid Energy Management (MEM) framework for a broad set of Microgrid applications that provides unified controls, protection, and energy management. This project contributed to the achievement of the U.S. Department of Energy’s Renewable and Distributed Systems Integration Program goals by developing a fully automated power delivery microgrid network that: - Reduces carbon emissions and emissions of other air pollutants through increased use of optimally dispatched renewable energy, - Increases asset use through integration of distributed systems, - Enhances reliability, security, and resiliency from microgrid applications in critical infrastructure protection, constrained areas of the electric grid, etc. - Improves system efficiency with on-site, distributed generation and improved economic efficiency through demand-side management.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2011

Carbon Characterization Laboratory Readiness to Receive Irradiated Graphite Samples

The Carbon Characterization Laboratory (CCL) is located in Labs C19 and C20 of the Idaho National Laboratory Research Center. The CCL was established under the Next Generation Nuclear Plant Project to support graphite and ceramic composite research and development activities. The research conducted in this laboratory will support the Advanced Graphite Creep experiments—a major series of material irradiation experiments within the Next Generation Nuclear Plant Graphite program. The CCL is designed to characterize and test low activated irradiated materials such as high purity graphite, carbon-carbon composites, silicon-carbide composite, and ceramic materials. The laboratory is fully capable of characterizing material properties for both irradiated and nonirradiated materials. Major infrastructural modifications were undertaken to support this new radiological facility at Idaho National Laboratory. Facility modifications are complete, equipment has been installed, radiological controls and operating procedures have been established and work management documents have been created to place the CCL in readiness to receive irradiated graphite samples.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2012

Annual Report for Los Alamos National Laboratory Technical Area 54, Area G Disposal Facility – Fiscal Year 2011

As a condition to the Disposal Authorization Statement issued to Los Alamos National Laboratory (LANL or the Laboratory) on March 17, 2010, a comprehensive performance assessment and composite analysis maintenance program must be implemented for the Technical Area 54, Area G disposal facility. Annual determinations of the adequacy of the performance assessment and composite analysis are to be conducted under the maintenance program to ensure that the conclusions reached by those analyses continue to be valid. This report summarizes the results of the fiscal year 2011 annual review for Area G. Revision 4 of the Area G performance assessment and composite analysis was issued in 2008 and formally approved in 2009. These analyses are expected to provide reasonable estimates of the long-term performance of Area G and, hence, the disposal facility's ability to comply with Department of Energy (DOE) performance objectives. Annual disposal receipt reviews indicate that smaller volumes of waste will require disposal in the pits and shafts at Area G relative to what was projected for the performance assessment and composite analysis. The future inventories are projected to decrease modestly for the pits but increase substantially for the shafts due to an increase in the amount of tritium that is projected to require disposal. Overall, however, changes in the projected future inventories of waste are not expected to compromise the ability of Area G to satisfy DOE performance objectives. The Area G composite analysis addresses potential impacts from all waste disposed of at the facility, as well as other sources of radioactive material that may interact with releases from Area G. The level of knowledge about the other sources included in the composite analysis has not changed sufficiently to call into question the validity of that analysis. Ongoing environmental surveillance activities are conducted at, and in the vicinity of, Area G. However, the information generated by many of these activities cannot be used to evaluate the validity of the performance assessment and composite analysis models because the monitoring data collected are specific to operational releases or address receptors that are outside the domain of the performance assessment and composite analysis. In general, applicable monitoring data are supportive of some aspects of the performance assessment and composite analysis. Several research and development (R and D) efforts have been initiated under the performance assessment and composite analysis maintenance program. These investigations are designed to improve the current understanding of the disposal facility and site, thereby reducing the uncertainty associated with the projections of the long-term performance of Area G. The status and results of R and D activities that were undertaken in fiscal year 2011 are discussed in this report. Special analyses have been conducted to determine the feasibility of disposing of specific waste streams, to address proposed changes in disposal operations, and to consider the impacts of changes to the models used to conduct the performance assessment and composite analysis. These analyses are described and the results of the evaluations are summarized in this report. The Area G disposal facility consists of Material Disposal Area (MDA) G and the Zone 4 expansion area. To date, all disposal operations at Area G have been confined to MDA G. Material Disposal Area G is scheduled to undergo final closure in 2015; disposal of waste in the pits and shafts is scheduled to end in 2013. In anticipation of the closure of MDA G, plans are being made to ship the majority of the waste generated at LANL to off-site locations for disposal. It is not clear at this time if waste that will be disposed of at LANL will be placed in Zone 4 or if disposal operations will move to a new location at the Laboratory. Separately, efforts to optimize the final cover used in the closure of MDA G are underway; a final cover design different than that adopted for the performance assessment and composite analysis will likely emerge from that investigation. All of these changes will require re-examination of the assumptions upon which the performance assessment and composite analysis are based and, in all likelihood, revision of those analyses.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2012

SystemBurn: Principles of Design and Operation, Release 2.0

As high performance computing technology progresses toward the progressively more extreme scales required to address critical computational problems of both national and global interest, power and cooling for these extreme scale systems is becoming a growing concern. A standardized methodology for testing system requirements under maximal system load and validating system environmental capability to meet those requirements is critical to maintaining system stability and minimizing power and cooling risks for high end data centers. Moreover, accurate testing permits the high end data center to avoid issues of under- or over-provisioning power and cooling capacity saving resources and mitigating hazards. Previous approaches to such testing have employed an ad hoc collection of tools, which have been anecdotally perceived to produce a heavy system load. In this report, we present SystemBurn, a software tool engineered to allow a system user to methodically create a maximal system load on large scale systems for the purposes of testing and validation.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2012

SystemBurn: Principles of Design and Operation Release 2.1

99 GENERAL AND MISCELLANEOUS↗