Towards Adaptive Decision Support: A Perspective from Intelligent and Annotated Visual Analytics for Exploring Big Urban Mobility Data
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Software is an increasingly important component in the pursuit of scientific discovery. Both its development and use are essential activities for many scientific teams. At the same time, very little scientific study has been conducted to understand, characterize, and improve the development and use of software for science. Computational science teams have diversified over time to include contributions from domain scientists who provide expertise in scientific and engineering disciplines, applied mathematicians and computer scientists who provide optimal algorithms and data structures, and software and data engineers who provide methodologies and tools adapted and adopted from other software domains. These diverse contributions have enabled tremendous advances in the pursuit of scientific discovery, even as models, computer architectures, and software environments have become more complicated. With this increasing diversity, we believe the next opportunity for qualitative improvement comes from applying the scientific method to understanding, characterizing, and improving how scientific software is developed and used. We believe that this pursuit requires expertise from computational scientists themselves, and from the cognitive and social sciences as well as the software engineering research community. As we look to increase the productivity and sustainability of the scientific-software-development-and-use cycle, a more systematic application of the scientific method to understand processes for software development and use will be a valuable tool to guide future work and result in more usable and sustainable software. This workshop will bring together computer scientists, software engineering researchers, computational scientists, applied mathematicians, social scientists, cognitive scientists, and others, to explore how we can conduct such systematic investigations, what can be learned, and how doing so will benefit the scientific enterprise. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees — from DOE, industry, and academia — will produce a report for ASCR that summarizes the findings of the workshop.
Energy storage, primarily in the form of electrochemical batteries, is critical for enabling integration of marine energy (e.g., power from waves and currents) with end-use applications at sea due to the periodicity of the resources and requirement of consistent, smooth power delivery. Powering high-latitude coastal or ocean-based observing systems has been identified as a high value-proposition use case, exemplifying the concept of Powering the Blue Economy. An existing power system implementation for such a platform uses solar panels coupled to rechargeable lithium-ion batteries, augmented by a non-rechargeable backup bank used to power heaters in winter months. As wave energy is a potential resource for powering this and similar use cases and is strongest when solar power is most limited, it was hypothesized that integration of wave power would alleviate some of the challenges in cold climates related to energy storage. In this work, we investigate the use case scenario in simulation and perform a comparative test of commercially-available lithium-ion battery chemistry formulations to determine the most appropriate choice for the application. The experiment compared the most commonly-used lithium-based battery types (NCM, NCA, and LFP) in laboratory conditions emulating a battery enclosure thermally coupled to freezing seawater using an industrial battery performance tester in PNNL's arctic simulation lab. Battery strings were repeatedly cycled (i.e., charged, discharged, rested) and their usable capacity was measured. Both NCM and NCA strings exhibited degradation upon cycling, while the LFP string maintained stable operation through over 700 complete cycles. Though lower in baseline capacity, LFP are recommended for this and similar low-temperature applications with access to high levels of bulk charging current (e.g., from high-energy wave events) and their use may reduce the cost and complexity of battery conditioning and protection apparatus.
Increasingly powerful and affordable computing has revolutionized scientific and scholarly discovery across a broad range of fields. Computing relies on software, which has been rapidly growing in scope, diversity, and complexity. At the same time, the methods, processes, and tools used to produce and utilize this essential software are often ad hoc, and the study and improvement of them are often done without the benefit of direct funding or prioritization. Consequently, concerns are growing about the productivity of the developers and users of scientific software, its sustainability, and the trustworthiness of the results that it produces. Increased investment, especially in the characterization and improvement of how scientific software is developed and used, is important for sustaining and improving the impact of software as the scope and complexity of scientific efforts expand. Without this investment, we face the risk of diminishing returns on our software investments because the demands for increased functionality, usability, reliability, and more will not be sufficiently met. The US Department of Energy Office of Science (DOE/SC) is at the forefront of modern software-enabled scientific discovery across numerous areas of computational, experimental, and observational science, including major investments in national user facilities that support these activities. For many years, DOE/SC software investments have provided tremendous value to the scientific community. We want to continue and further improve the value of DOE/SC software efforts by using a scientific approach to understanding and improving how scientific software is developed and used. In December 2021, the DOE/SC Office of Advanced Scientific Computing Research (ASCR) convened a workshop on basic research needs for the Science of Scientific-Software Development and Use (SSSDU). Through keynote presentations, lightning talks, and breakout groups, which built on insights from 124 pre-workshop position papers, participants discussed the current practice of software development, maintenance, evolution, and use, and considered how the scientific method could be used to examine these practices and develop more evidence-based approaches to enhance the impact of software and computing on all areas of science. Workshop participants identified three priority research directions (PRDs) and three important crosscutting themes that center on the following overarching insight: Software has become an essential part of modern science, impacting discoveries, policy, and technological development. To maintain and improve confidence in science delivered via software, we must improve the processes and tools that help us create and use software, and this enhancement requires a deep understanding of the diverse array of teams and individuals doing the work.
The HyRAM+ software toolkit provides a basis for conducting quantitative risk assessment and consequence modeling for hydrogen, methane, and propane systems. HyRAM+ is designed to facilitate the use of state-of-the-art models to conduct robust, repeatable assessments of safety, hazards, and risk. HyRAM+ integrates deterministic and probabilistic models for quantifying accident scenarios, predicting physical effects, characterizing hazards (thermal effects from jet fires, overpressure effects from delayed ignition), and assessing impacts on people. HyRAM+ is developed at Sandia National Laboratories to support the development and revision of national and international codes and standards, and to provide developed models in a publicly-accessible toolkit usable by all stakeholders. This document provides a description of the methodology and models contained in HyRAM+ version 4.1. The two most significant changes for HyRAM+ version 4.1 from HyRAM+ version 4.0 are direct incorporation of unconfined overpressure into the QRA calculations and modification of the models for cryogenic liquid flow through an orifice. In QRA mode, the user no longer needs to input peak overpressure and impulse values that were calculated separately; rather, the unconfined overpressure is estimated for the given system inputs, leak size, and occupant location. The orifice flow model now solves for the maximum mass flux through the orifice at constant entropy while conserving energy, which does not require a direct speed of sound calculation. This does not affect the mass flow for all-gaseous releases; the method results in the same speed of sound for choked flow. However, this method does result in a higher (and more realistic) mass flow rate for a given leak size for liquid releases than was previously calculated.
The global composite industry generates large quantities of waste and which mostly end as landfill due to lack of meaningful end-use applications for the multiple waste streams. In a recent report by the Electric Power Research Institute (EPRI), waste generated by the wind industry could reach 370,000 tons a year of composite wind energy blades being decommissioned and scrapped. Wind energy is just one major industry utilizing composite materials. The waste generated by industry includes End-of-Life (EoL) materials and manufacturing process scrap. GreenTex Solutions has developed a unique and innovative technology to recycle the composite waste streams in a range of forms made from production waste and EoL materials. This includes manufacturing waste materials such as dry chopped fiber tow, loose fibers, shredded fibers from reinforcement fabrics, cured/semi-cured prepregs, and it also includes fully-cured composite structure waste (such as edge trims from cured parts) from manufacturing aircraft, automobiles, wind blades, boats, and composite cylinders (tanks). Current recycling methods involve recovering the structural fiber by removing the matrix resin through methods such as pyrolysis. The resulting fibers are used in injection molding or wet laid nonwoven mats and other usable forms. The GreenTex technology bypasses these intermediate steps to create the lowest possible recycling processing costs and the lowest embodied energy/CO2 emissions. The end-product from the GreenTex technology is a finished industrial composite part/application versus intermediate fibers or fabrics. The GreenTex manufacturing process enables cross-industry reuse of recycled feedstock by taking waste from multiple industries (wind energy, aerospace, marine, etc.) and recycles the waste into a product used in other industries. The initial target market application is structural flooring for intermodal shipping containers and truck bodies. One of the team’s key partners is Wabash National which produced 29,000 truck bodies in 2019. The current flooring system is comprised of solid oak “butcher board” laminated panels. Additionally, Mediterranean Shipping Containers (MSC) transports over 1.8 million twenty-foot equivalent units per year in intermodal shipping containers. The current container floor is laminated hardwood that is harvested from the rain forests of Central and South America. The project is to develop a flooring system made from recycled composites that can be qualified for both companies (Wabash and MSC). Initial prototypes validated that the recycled composites panels are lighter and thinner with much higher mechanical strength. These results suggest a typical truck trailer would have 20% lower tare weight. The GreenTex technology is not limited to flooring and is widely applicable to other transportation elements such as walls, roof elements, cab areas and related structural components. Under this project different composite waste streams were evaluated and then combined to develop a formulation that would meet the targeted performance criteria for a flooring system. Wet compression molding was used to fabricate plaques at different tonnage using various composite waste streams. The plaques were tested for flexure and impact.
Lightweight composites are of increasing need to enable reduced fuel usage, reduced carbon emissions and increased range in air and ground transportation. The superior weight savings of carbon fiber thermoset composites are impeded by material and production costs and the limited options available for composite repair and recycle. The materials recovery and recycling sector is currently overwhelmed by an abundance of low-value materials and limited market opportunities for downcycled content, rendering landfilling a more attractive alternative. Vitrimers represent a new paradigm for repairable and recyclable thermosets, but this relatively new technology will require development, including government investment, to reduce risks for its adoption by aerospace and automotive OEMs. The overall goal of the project is to create recyclable carbon fiber composites using vitrimer resins that are more energy efficient to produce and have improved properties over baseline technology. The targeted composites will retain their tensile strength after multiple recycling and reprocessing steps. In addition, monomer will be recoverable through depolymerization and re-usable carbon fibers will be retrieved.
Distributed energy resource (DER) systems feature complex, data-driven communications networks that require careful system coordination and constant vigilance to ensure that grid assets are secure. Because DERs are an important component of the decarbonization strategy, agencies need to secure energy data that could implicate issues of national security if compromised. To help federal energy managers assess, monitor, and manage cybersecurity while achieving decarbonization, the National Renewable Energy Laboratory's (NREL's) Distributed Energy Resource Cybersecurity Framework (DER-CF) offers a comprehensive, web-based assessment tool focusing on cyber governance or policies, technical management, and physical security. The DER-CF currently presents users with a series of pertinent cybersecurity questions that are used to generate a site-specific report and recommendations. This paper outlines a plan to integrate the DER-CF with another key asset-NREL's cyber range-to visualize cybersecurity resilience and compliance and to enhance the usability and accessibility of the DER-CF for federal facility energy managers and planners. This integration will result in a visualization environment to interpret and interact with compliance data. Its development will include regular conversations with stakeholders to assess the effectiveness of these efforts, refine the visualization capability, and ensure its value to our partners.
Element6 has come out of a two year production pause (pre-COVID) with material that lacks their previous QC – some is excellent, but screening is needed. Applied Diamond can now make usable polycrystalline material, for applications not requiring absolute flux calibration. A large area possible (1cm 2 ). Great Lakes Crystal Technology has made great progress in two years, but still needs development to become a trusted supplier of single crystal material. LANL staff (Dongsung Kim) has developed proficient lithography and bonding expertise at CINT to make devices from vendor supplied material. LANL staff has continued and expanded capabilities for device testing at NSLS-II.
Accelerating intelligent deployment of solar energy technologies demands accurate system modeling every step of the way. From project development to policy research, grid integration studies to development of novel technologies, industry and researchers alike need validated, transparent, easy-to-use, extensible, cutting-edge, and accurate models of both the performance and financing of solar systems. The System Advisor Model (SAM) and PVWatts tools provide a platform to fill that need. The overarching goal of this set of software tools is to enable accurate PV system modeling across the industry, and our usage metrics indicate that we continue to succeed in that endeavor, with a user starting SAM every 2 minutes globally, and over 17 million PVWatts hits per month. This project leveraged DOEs past investment in the SAM and PVWatts platforms to continue to provide valuable and extensible PV, battery, and financial modeling resources to the larger solar community. We pursued multiple avenues in parallel: software maintenance and technical support that are foundational to the continued usability of the SAM and PVWatts platforms; platform and PV model improvements and stakeholder engagement activities that are core to the continued relevance of the platforms; and open source activities to foster the continued creation of a vibrant open-source community around the SAM and PVWatts tools, which opens up exciting new opportunities for industry interaction.
Boiler failure could cause loss of life and safety issues, cost hundreds of thousands of dollars in equipment repairs, property damage and production losses, and drive up the cost of electric power. Boiler maintenance is challenging and risky for inspectors working on scaffolding in confined hazardous spaces inside of a boiler and sometimes the space is hard to access. The operation is also time-consuming due to the large area of vertical structures for inspection and the tremendous effort needed for scaffolding. Recently, the use of robotics (e.g., drones and crawlers) in power plants for maintenance is growing rapidly. However, the existing robotics solutions show two notable technological gaps: no live repair capability, and no Artificial Intelligence (AI) for smart autonomy. The objective of this project is to develop an integrated autonomous robotic platform that is equipped with compact non-destructive evaluation (NDE) sensors to perform live inspection, operates onboard repair devices to perform live repair, and uses AI for intelligent data fusion and predictive analysis for automated and smart spatiotemporal inspection, analysis and repair of the furnace walls in coal-fired boilers. The approach to achieve the objective includes developing NDE sensors with signal processing techniques, designing and evaluating repair devices for robots based on fusion and solid-state technologies, and an autonomous robotic platform that can attach to and navigate on boiler furnace walls using magnetic drive tracks. The robot is also powered by AI to automate data gathering (e.g., 3D mapping and damage localization) and predictive analysis. This project has advanced the state-of-the-art by providing technological breakthroughs including compact NDE and repair tools for robots, AI capabilities for smart autonomy, and a robotic platform for automated boiler maintenance. This project has great potential to result in significant benefits including limiting or eliminating the need to send operators to assess difficult-to-access or hazardous areas, enabling automated live inspection and repair, avoiding time consuming scaffolding (especially for partial maintenance during unplanned outage), collecting comprehensive and well-organized data smartly, and avoiding or limiting the need for onsite or remote piloting technicians. The impacts can be tremendous in terms of the time and cost savings, reducing the risk for human operators, and increasing boiler reliability, usability, and efficiency. In addition, by developing the new technologies on the autonomous inspection and repair robot, by involving multiple undergraduate and graduate students working together with the faculty members on this project, and by generating knowledge and building up collaborations with industrial partners, this effort will significantly update the education capabilities, support long-term fundamental research, and maintain the leadership of Colorado School of Mines and Michigan State University in energy fields.
Thorium has been considered as a possible alternative to uranium for nuclear fuel for many decades. It is three to four times more abundant in the earth than uranium and produces significantly less long-lived transuranic nuclear waste. Some claim thorium poses fewer proliferation concerns than other fuel types largely due to 232 U buildup (and associated high energy gamma-emitting decay products) in the irradiated thorium fuel. However, to fully explore potential proliferation concerns, generation and subsequent decay of 233 Pa produced in the reactor core still must be studied. With its half-life of 27 days, 233 Pa decays to 233 U, which is an International Atomic Energy Agency (IAEA) defined special fissionable material that can be used for nuclear weapons production. With more research being dedicated to thorium-fueled reactors, and several of these reactor designs possessing online fuel processing (allowing for on-site protactinium separation), it is important to understand this potential proliferation pathway. In particular, it is theoretically possible to extract protactinium from the irradiated fuel salt before it decays into 233 U. This hypothetical potential diversion can become an even greater proliferation concern if the extracted protactinium is purified through a second separation of protactinium approximately ten days later to remove the short half-life decay products of 232 Pa and 234 Pa, thus resulting in a higher concentration of the 233 Pa isotope, which decays into weapons usable 233 U with hardly any 232 U or 234 U in it. To estimate the concern of this potential proliferation challenge of thorium, different nuclear material accountancy techniques were reviewed for their viability to quantify 233 Pa if extracted from used thorium fuel. Characteristics of interest included technology maturity, cost, precision, and time taken to acquire results. Some technologies, like hybrid K-edge densitometry and passive gamma spectroscopy, appear to be viable techniques based on current literature. Due to the limited scope of this project, only passive gamma spectroscopy was further investigated. Three different reactor types (PWR, CANDU, MSR) were modeled with mixed thorium-uranium oxide fuels that were burned until the fuel was spent. The protactinium in the used fuel was extracted at the time of shutdown and the change in isotopic content of the protactinium quantified. Gamma spectroscopy simulations were performed for the protactinium isotopes and their decay products at various decay times. Given the simplicity of the models and large assumptions made (e.g. no background, no shielding, no self-attenuation), the initial results indicate that though 233 Pa is detectible for all the reactor types modeled at all decay times (0 to 300 days), more work should be done with higher fidelity models.
There is an imminent need for the existing nuclear power plants to reduce their operating and maintenance (O&M) costs to remain economically viable. Digital technology, including automation, provides a significant opportunity for the existing nuclear power plant fleet to transform the way in which work is accomplished, reducing O&M costs, and allowing the fleet to remain economically competitive. One notable opportunity to significantly reduce O&M costs pertains to modifications to the plant equipment and main control room (MCR). Existing instrumentation and control (I&C) technologies in the MCR are highly analog, costly to operate and maintain, and demand a high cognitive and physical workload from plant staff (i.e., operators). Digitalizing the MCR has a range of broad economic benefits, including improved plant performance and reduced manual work. Further, digital I&C systems can fundamentally change the way in which plant staff operate the plant; this is the concept of operation. Human-technology integration is important to ensure that impacts to the concept of operation are done in a way that account for capabilities of people and technology. Human-technology integration employs human factors engineering (HFE) methods and principles to maximize the benefits of digital technology, reducing human error, improving overall decision-making and usability. The U.S. Department of Energy Light Water Reactor Sustainability Program is applying human-technology integration research to ensure digital technologies are safe, reliable, and efficient. This paper documents the demonstration of the human-technology guidance developed by the Light Water Reactor Sustainability Program from a first-of-a-kind digital I&C upgrade, specifically addressing function analysis and allocation for a new digital I&C system that included changes in automation levels. The program’s specific approach is included in this work, following lessons learned. This document serves as a resource for industry to follow in applying human-technology integration and HFE to digital modifications, specific to function analysis and allocation. The lessons learned should be considered in the planning and execution of HFE activities that support such digital modifications.
Two balls were dropped approximately 150 m down an open borehole as part of an investigation into the aftershocks from a 51 ton TNT-equivalent chemical explosion. The ball drop sources, a concrete-filled basketball and a bowling ball, were intended to mimic falling debris within an underground explosion borehole and cavity. Falling debris or sloughing of the borehole and cavity walls is thought to be one of the sources of explosion aftershocks. The signals from the ball drop sources were recorded by the same seismic network that monitored the aftershocks of the chemical explosion, so the ball drop recordings were used as templates to search through the continuous stream of aftershocks and detect correlated signals as a proportion of all aftershocks. The search resulted in only four similar event recordings out of the thousands of detected aftershocks. A synthetic test showed that the small, high-frequency ball drop templates were limited to producing highly correlated detections for events occurring in a small region around the impact location at 150 m depth. The high-frequency templates were necessary since the small ball drop signals were only above the noise at frequencies greater than 10 Hz. Unfortunately, the impact location is where the borehole was filled with sand in preparation for the subsequent chemical explosion in the test series, making it 150 m above the explosion created cavity centered at 300 m depth. This puts the ball drop templates 150 m away from the cavity, where many more events from falling debris would be expected. Further synthetic tests confirmed events emanating from the cavity 150 m below the impact site would have correlated with the lower frequency template and been detected had the template been usable below 10 Hz. Therefore, we conclude that the four detected events were most probably falling debris within the open borehole that impacted the floor at 150 m depth just as the ball drop sources had, and that this type of explosion aftershock mechanism comprises less than 1% of all explosion aftershocks.
Writing software is difficult. However, writing complex, well tested and designed, and functionally correct software is incredibly difficult. An entire field of study is devoted to the validation and verification of software to address this problem, and in this paper we analyze the landscape of currently available third party software. We have divided our analyses into three separate subsections with regards to software validation: formal methods, static analysis, and test generation. Formal verification is the most complex method in which to validate software correctness, but also the most thorough as it truly validates the mathematical validity of the source code. Static analysis generally is relegated to abstract syntax tree traversal techniques to find errors related to faulty software such as memory leaks or stack overflow issues. Automatic test generation is similar in implementation to static analysis, but pushes a bit further in verifying the boundedness of function inputs and outputs with regards to annotated or parsed criteria. The crux of this report is to analyze and describe the software tools that implement these techniques to validate and verify software. Pros and cons related to installation, utilization, and capabilities of the frameworks are described, and reproducible examples are provided with a focus on usability. The initial survey concluded that the most interesting tools of note are Z3, Isabelle/HOL, and TLA+ with regards to formal verification; and Infer, Frama-C, and SonarQube with regards to static analysis. With these tools in mind, a final conjecture is provided that describes future avenues of utilizing these tools for developing a verification framework to assist in validating existing software at Sandia National Laboratories.
LANL lists several NJOY priorities for the future, including the maintenance of NJOY2016 for the foreseeable future, as well as the delivery of usable NJOY21 components.
This report describes improvements made to the solid mechanics formulation in the MOOSE open source finite element simulation environment and the open source Nuclear Engineering Material model Library (NEML) for mechanical constitutive models. The focus of these improvements is to improve the usability and performance of simulations involving one or both pieces of software. Specifically, this work completes a new system for solid mechanics simulations in the MOOSE ecosystem providing exact linearizations and optimal (quadratic) convergence, for a variety of coordinate systems and material types, including large deformation simulations. This work then provides users a framework to build highly efficient mechanical simulations of structures or materials or to couple in additional MOOSE physics modules to build complex, scalable multiphysics simulations.
The PRO-X program is actively supporting the design of nuclear systems by developing a framework to both optimize the fuel cycle infrastructure for advanced reactors (ARs) and minimize the potential for production of weapons-usable nuclear material. Three study topics are currently being investigated by Sandia National Laboratories (SNL) with support from Argonne National Laboratories (ANL). This multi-lab collaboration is focused on three study topics which may offer proliferation resistance opportunities or advantages in the nuclear fuel cycle. These topics are: 1) Transportation Global Landscape, 2) Transportation Avoidability, and 3) Parallel Modular Systems vs Single Large System (Crosscutting Activity).