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NASA NTRS2022

Making or Breaking a Rover- Systems Engineering Parameters On-Board the Mars 2020 Perseverance Rover

On February 18, 2021, Perseverance, NASA’s Jet Propulsion Laboratory’s (JPL’s) Mars 2020 Rover, successfully landed on Mars with all systems nominal, despite the risk surrounding the over 200,000 internal flight parameters that had to be properly configured. The Perseverance team defines these parameters as software variables that are configurable, commandable and retrievable from Earth. In 2015, the Mars 2020 project leaders focused on improving systems engineering of parameters based on their experiences from parameter management on previous Mars rovers (Curiosity, Opportunity, Spirit, and Pathfinder) and parameter failures of past missions, such as the mission-ending parameter of the Mars Climate Orbiter. The new rigorous development process allowed for efficient certification and effective implementation of the parameters, allowing the rover to approach and land on the red planet (the most challenging phase of the mission) with zero parameter issues. Although successful, the Perseverance team learned many lessons for how to better manage parameters for the continued surface operations of the Mars 2020 mission and future missions. This paper will discuss eight parameter-management topics for the Perseverance Mission. The first is parameter definition: how we define parameters on our mission, where they are physically located on the vehicle, and why we have so many of them. The second topic is the updated parameter flight software module from Curiosity, including details on the 99% reduction in parameter commands, new bulk configuration capabilities, and improved parameter traceability. The third topic is parameter selection for different mission phases; this includes improving and tweaking our preferred parameter settings until they become certification candidates and managing parameter configurations based on test venue throughout the mission life cycle. The fourth topic is our flight certification process; this includes certification of flight values for four different epochs in the mission: Launch, Entry Decent and Landing (EDL) - 6days, Landing + 5 Sols (Martian Days, still on Cruise Flight Software), and once are on Surface Flight Software (FSW). The fifth topic covers in-flight command implementation, along with details on testing, validation, and verification of those commands. In the sixth section, we will explain our use of open-source management tools, including how we used GitHub for version control and management approvals. The seventh topic will describe the ground tools used in operations, including capabilities of the in-house built tool called Parasol. The eighth and final topic will dig into lessons learned for improving parameter management in the future of this mission and others.

Roth, Brian↗

NASA NTRS1999

Evaluation of Spacecraft Shielding Effectiveness for Radiation Protection

The potential for serious health risks from solar particle events (SPE) and galactic cosmic rays (GCR) is a critical issue in the NASA strategic plan for the Human Exploration and Development of Space (HEDS). The excess cost to protect against the GCR and SPE due to current uncertainties in radiation transmission properties and cancer biology could be exceedingly large based on the excess launch costs to shield against uncertainties. The development of advanced shielding concepts is an important risk mitigation area with the potential to significantly reduce risk below conventional mission designs. A key issue in spacecraft material selection is the understanding of nuclear reactions on the transmission properties of materials. High-energy nuclear particles undergo nuclear reactions in passing through materials and tissue altering their composition and producing new radiation types. Spacecraft and planetary habitat designers can utilize radiation transport codes to identify optimal materials for lowering exposures and to optimize spacecraft design to reduce astronaut exposures. To reach these objectives will require providing design engineers with accurate data bases and computationally efficient software for describing the transmission properties of space radiation in materials. Our program will reduce the uncertainty in the transmission properties of space radiation by improving the theoretical description of nuclear reactions and radiation transport, and provide accurate physical descriptions of the track structure of microscopic energy deposition.

Cucinotta, Francis A.↗

DOE OSTI2016

SU-F-J-174: A Series of Computational Human Phantoms in DICOM-RT Format for Normal Tissue Dose Reconstruction in Epidemiological Studies

Purpose: Epidemiological studies of second cancer risk in radiotherapy patients often require individualized dose estimates of normal tissues. Prior to 3D conformal radiation therapy planning, patient anatomy information was mostly limited to 2D radiological images or not even available. Generic patient CT images are often used in commercial radiotherapy treatment planning system (TPS) to reconstruct normal tissue doses. The objective of the current work was to develop a series of reference size computational human phantoms in DICOM-RT format for direct use in dose reconstruction in TPS. Methods: Contours of 93 organs and tissues were extracted from a series of pediatric and adult hybrid computational human phantoms (newborn, 1-, 5-, 10-, 15-year-old, and adult males and females) using Rhinoceros software. A MATLAB script was created to convert the contours into the DICOM-RT structure format. The simulated CT images with the resolution of 1×1×3 mm3 were also generated from the binary phantom format and coupled with the DICOM-structure files. Accurate volumes of the organs were drawn in the format using precise delineation of the contours in converted format. Due to complex geometry of organs, higher resolution (1×1×1 mm3) was found to be more efficient in the conversion of newborn and 1-year-old phantoms. Results: Contour sets were efficiently converted into DICOM-RT structures in relatively short time (about 30 minutes for each phantom). A good agreement was observed in the volumes between the original phantoms and the converted contours for large organs (NRMSD<1.0%) and small organs (NRMSD<7.7%). Conclusion: A comprehensive series of computational human phantoms in DICOM-RT format was created to support epidemiological studies of second cancer risks in radiotherapy patients. We confirmed the DICOM-RT phantoms were successfully imported into the TPS programs of major vendors.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1999

NASA HPCC Technology for Aerospace Analysis and Design

The Computational Aerosciences (CAS) Project is part of NASA's High Performance Computing and Communications Program. Its primary goal is to accelerate the availability of high-performance computing technology to the US aerospace community-thus providing the US aerospace community with key tools necessary to reduce design cycle times and increase fidelity in order to improve safety, efficiency and capability of future aerospace vehicles. A complementary goal is to hasten the emergence of a viable commercial market within the aerospace community for the advantage of the domestic computer hardware and software industry. The CAS Project selects representative aerospace problems (especially design) and uses them to focus efforts on advancing aerospace algorithms and applications, systems software, and computing machinery to demonstrate vast improvements in system performance and capability over the life of the program. Recent demonstrations have served to assess the benefits of possible performance improvements while reducing the risk of adopting high-performance computing technology. This talk will discuss past accomplishments in providing technology to the aerospace community, present efforts, and future goals. For example, the times to do full combustor and compressor simulations (of aircraft engines) have been reduced by factors of 320:1 and 400:1 respectively. While this has enabled new capabilities in engine simulation, the goal of an overnight, dynamic, multi-disciplinary, 3-dimensional simulation of an aircraft engine is still years away and will require new generations of high-end technology.

Schulbach, Catherine H.↗

DOE OSTI2019

Correlated Synthetic Time Series Generation using Fourier and ARMA

As the contribution of renewable energy grows in electricity markets, the complexity nuclear’s place within the energy mix increases, and likewise the need for robust simulation techniques. While decades of wind, solar, and demand pro- files can sometimes be obtained, this is too few samples to provide a statistically meaningful analysis of a system with baseload, peaker, and renewable generation. Synthetic time series generation presents itself as a suitable methodology to meet this need. One approach for synthetic series generation is training a model using Fourier series decomposition for seasonal patterns and Auto-Regressive Moving Average models (ARMA) to describe time-correlated statistical noise about the seasonal patterns. When combined, the Fourier plus ARMA (FARMA) model has been shown to provide an infinite set of independent, identically-distributed sample time series with the same statistical properties as the original data [1]. When considering an energy mix with renewable electricity production, several time series of energy, grid, and weather measurements are needed for each synthetic year modeled to statistically comprehend the efficiency of any given energy mix. These cannot be considered independent series in a given synthetic year. To capture and reproduce the correlations that might exist in the measured histories, the ARMA can further be extended as a Vector ARMA (VARMA). In the VARMA algorithm, covariance in statistical noise is captured both within a history as part of the autoregressive moving average, and with respect to the other variables in the time series. In this work the implementation of the Fourier VARMA in the RAVEN uncertainty quantification and risk analysis software framework [2] is presented, along with examples of correlated synthetic history generation.

97 MATHEMATICS AND COMPUTING↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

activity planning↗

NASA NTRS2022

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗

DOE OSTI2012

Advanced Computational Methods for Security Constrained Financial Transmission Rights

Financial Transmission Rights (FTRs) are financial insurance tools to help power market participants reduce price risks associated with transmission congestion. FTRs are issued based on a process of solving a constrained optimization problem with the objective to maximize the FTR social welfare under power flow security constraints. Security constraints for different FTR categories (monthly, seasonal or annual) are usually coupled and the number of constraints increases exponentially with the number of categories. Commercial software for FTR calculation can only provide limited categories of FTRs due to the inherent computational challenges mentioned above. In this paper, first an innovative mathematical reformulation of the FTR problem is presented which dramatically improves the computational efficiency of optimization problem. After having re-formulated the problem, a novel non-linear dynamic system (NDS) approach is proposed to solve the optimization problem. The new formulation and performance of the NDS solver is benchmarked against widely used linear programming (LP) solvers like CPLEX™ and tested on both standard IEEE test systems and large-scale systems using data from the Western Electricity Coordinating Council (WECC). The performance of the NDS is demonstrated to be comparable and in some cases is shown to outperform the widely used CPLEX algorithms. The proposed formulation and NDS based solver is also easily parallelizable enabling further computational improvement.

Environmental Molecular Sciences Laboratory↗

NASA NTRS2006

Spitzer Observatory Operations -- Increasing Efficiency in Mission Operations

This paper explores the how's and why's of the Spitzer Mission Operations System's (MOS) success, efficiency, and affordability in comparison to other observatory-class missions. MOS exploits today's flight, ground, and operations capabilities, embraces automation, and balances both risk and cost. With operational efficiency as the primary goal, MOS maintains a strong control process by translating lessons learned into efficiency improvements, thereby enabling the MOS processes, teams, and procedures to rapidly evolve from concept (through thorough validation) into in-flight implementation. Operational teaming, planning, and execution are designed to enable re-use. Mission changes, unforeseen events, and continuous improvement have often times forced us to learn to fly anew. Collaborative spacecraft operations and remote science and instrument teams have become well integrated, and worked together to improve and optimize each human, machine, and software-system element.

operational efficiency↗

NASA NTRS2019

Workforce for the Future Development of Space Access Vehicles

The development of advanced vehicles that will travel between planetary surfaces with atmospheres and space requires the availability of experimental and computational capabilities that accomplish the research leading to new technologies and the development, test, and evaluation (RDT&E) of new flight systems. The United States is at risk of not having the required RDT&E workforce – qualified and in sufficient numbers – in place and ready to meet the future market’s commercial and defense needs. Systemic challenges include uncertain Federal budgets that limit and interrupt government research and development, the projectized nature of new space access systems that drive boom/bust cycles, an aging aerospace workforce (compounded by a mid-age demographic gap), limited to declining investment in sustaining and advancing experimental and computational tools infrastructure, lack of standards for sharing (and leveraging) data, dramatically changing technologies, changing social norms, and potentially large increases in commercial market needs. Flight systems have mission-based trajectories to and from space and designers must ensure risk is properly assessed across the entire trajectory. Thus, physics questions must be answered at each stage of flight, which requires a suite of experimental and computational tools. The RDT&E workforce utilizing these tools include subject matter experts from the producers, interested in acquiring data and information on the product, and from the capabilities being utilized, interested in addressing the product customer’s needs (providing robust data collection techniques, data quality, timeliness – available when needed, efficient with cost management, and teaming on data analysis). This requires a range of skills – in addition to aerospace, other engineers, and software developers, a highly trained and certified craft and technician workforce is critical to future success. This paper will present a human resources construct that addresses the system of needs for people – including, but more than just technical skills and an application of that construct in the hypersonic Test and Evaluation (T&E) community. This is part of a larger AIAA effort to document challenges and associated best practices for the aerospace RDT&E workforce.

Steven C Dunn↗

DOE OSTI2012

LLNL ARRA Report on CCSI Uncertainty Quantification Capabilities with Applications on MEA Process Models

The Carbon Capture Simulation Initiative (CCSI) is a partnership among national laboratories, industry and academic institutions that will develop and deploy state-of-the-art computational modeling and simulation tools to accelerate the commercialization of carbon capture technologies from discovery to development, demonstration, and ultimately the widespread deployment to hundreds of power plants. The CCSI Toolset will provide end users in industry with a comprehensive, integrated suite of scientifically validated models with uncertainty quantification, optimization, risk analysis and decision making capabilities. The CCSI Toolset will incorporate commercial and open-source software currently in use by industry and will also develop new software tools as necessary to fill technology gaps identified during execution of the project. The CCSI Toolset will (1) enable promising concepts to be more quickly identified through rapid computational screening of devices and processes; (2) reduce the time to design and troubleshoot new devices and processes; (3) quantify the technical risk in taking technology from laboratory-scale to commercial-scale; and (4) stabilize deployment costs more quickly by replacing some of the physical operational tests with virtual power plant simulations. The goal of CCSI is to deliver a toolset that can simulate the scale-up of a broad set of new carbon capture technologies from laboratory scale to full commercial scale. To provide a framework around which the toolset can be developed and demonstrated, we will focus on three Industrial Challenge Problems (ICPs) related to carbon capture technologies relevant to U.S. pulverized coal (PC) power plants. Post combustion capture by solid sorbents is the technology focus of the initial ICP (referred to as ICP A). The goal of the uncertainty quantification (UQ) task (Task 6) is to provide a set of capabilities to the user community for the quantification of uncertainties associated with the carbon capture processes. As such, we will develop, as needed and beyond existing capabilities, a suite of robust and efficient computational tools for UQ to be integrated into a CCSI UQ software framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Cyber risk assessment and investment optimization using game theory and ML-based anomaly detection and mitigation for wide-area control in smart grids

The electric power grid is increasingly becoming susceptible to cyber attacks that exploit vulnerabilities in the smart grid control, information, and physical layers. Successful cyber attacks can have catastrophic impacts on the social and economic well-being of any nation all over the globe. It has, thus, become imperative to secure the smart grid against such adversarial actions to ensure stable, secure, and reliable operation of the grid. The existing research and industry practices prove to be inadequate in terms of providing pragmatic and effective defense methodologies and measures for long-term cybersecurity planning and real-time cybersecurity for grid operation. For example, existing works lack models that incorporate uncertain behavior of cyber-attackers and pragmatic defense measures for cyber risk assessment and cybersecurity investment optimization which often provide unreliable and strictly qualitative solutions to these problems. At the same time, with the growing number of cyber incidents in the grid, there still exists a need to develop attack-resilient algorithms for wide-area monitoring, protection, and control (WAMPAC) applications like the wide-area voltage control systems (WAVCS) for Flexible AC Transmissions Systems (FACTS) that lack in scalable and feasible solutions from the cybersecurity perspective. This dissertation proposes novel models and methodologies for: (1) Cybersecurity planning, and (2) Cybersecurity for system operation. The cybersecurity planning is achieved through cyber risk assessment and cybersecurity resource investment optimization for long-term cybersecurity of the grid using game theory and attack-defense trees. Cybersecurity for system operation consists of development of cyber anomaly detection and mitigation algorithms for flexible AC transmission system (FACTS) controller-based wide-area voltage control systems (WAVCS) using machine learning (ML), and software defined networking-based moving target defense network routing for achieving real-time cyber-physical security for grid operations. This is followed by hardware-in-the-loop (HIL) implementation and evaluation of these attack prevention, detection, and mitigation algorithms and methodologies showcasing their feasibility in a close to real-world environment. For cybersecurity planning, a novel approach involving a combination of game theory and attack defense trees (ADT) for optimal cybersecurity resource allocation in the smart grid is proposed. This methodology involves modeling of the cyber-physical smart grid substations as ADTs, defining attacker costs, defense costs, and attack probabilities for attack access points. Using game theoretical formulation, optimal defense strategies for the defender of the system to invest cybersecurity resources in the grid are obtained. Additionally, a game-theoretic framework is developed for quantitative cyber-physical risk assessment of the grid under a dynamically changing cyber threat space and uncertain behavior of cyber attackers which is further used to optimize investments in the smart grid's cybersecurity resources. The attacker, defender, and the smart grid system are modeled while incorporating attacker-stochasticity and federal guidelines for smart grid cybersecurity. This allows quantification of threat, vulnerabilities, and attack impact of the grid for quantitative risk assessment. The defender's budget to invest in the security resources in the grid is optimized based on the strategies leading to minimum system risk. The evaluation of the proposed solutions highlight the feasibility for practical implementation of these methodologies and algorithms in the smart grid, while taking the federal requirements and guidelines for smart grid security into consideration. For achieving cybersecurity for system operation, attack prevention, detection, and mitigation algorithms and methodologies are developed specifically for FACTS-based WAVCS. Anomaly detection and mitigation in the WAVCS are achieved using algorithms based on machine learning which involves offline training and testing of ML models with CPS datasets incorporating physics-based features that allow accurate distinction between system faults and cyber attacks. For attack prevention, a methodology based on software defined network (SDN)-based moving target defense (MTD) network routing is proposed that enables prevention of Denial of Service (DoS) type attacks on the smart grid communication system. Subsequently, these methodologies and algorithms are implemented and evaluated on an HIL testbed that allows for real-time attack prevention, detection, and mitigation of emulated cyber attacks on the WAVCS in a close to real-world environment. The results show highly accurate and efficient performance of the implemented algorithms and methodologies with the smart grid system operating within the NERC's system operation limits even in the presence of DoS and data integrity cyber attacks. This work opens up future research opportunities in other directions such as (1) Expanding cybersecurity planning methodologies to real-time cyber contingency analysis with different game formulations; and (2) Applying the cybersecurity for system operation algorithms to broader categories of wide-area control applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2009

Recent Electric Propulsion Development Activities for NASA Science Missions

(The primary source of electric propulsion development throughout NASA is managed by the In-Space Propulsion Technology Project at the NASA Glenn Research Center for the Science Mission Directorate. The objective of the Electric Propulsion project area is to develop near-term electric propulsion technology to enhance or enable science missions while minimizing risk and cost to the end user. Major hardware tasks include developing NASA s Evolutionary Xenon Thruster (NEXT), developing a long-life High Voltage Hall Accelerator (HIVHAC), developing an advanced feed system, and developing cross-platform components. The objective of the NEXT task is to advance next generation ion propulsion technology readiness. The baseline NEXT system consists of a high-performance, 7-kW ion thruster; a high-efficiency, 7-kW power processor unit (PPU); a highly flexible advanced xenon propellant management system (PMS); a lightweight engine gimbal; and key elements of a digital control interface unit (DCIU) including software algorithms. This design approach was selected to provide future NASA science missions with the greatest value in mission performance benefit at a low total development cost. The objective of the HIVHAC task is to advance the Hall thruster technology readiness for science mission applications. The task seeks to increase specific impulse, throttle-ability and lifetime to make Hall propulsion systems applicable to deep space science missions. The primary application focus for the resulting Hall propulsion system would be cost-capped missions, such as competitively selected, Discovery-class missions. The objective of the advanced xenon feed system task is to demonstrate novel manufacturing techniques that will significantly reduce mass, volume, and footprint size of xenon feed systems over conventional feed systems. This task has focused on the development of a flow control module, which consists of a three-channel flow system based on a piezo-electrically actuated valve concept, as well as a pressure control module, which will regulate pressure from the propellant tank. Cross-platform component standardization and simplification are being investigated through the Standard Architecture task to reduce first user costs for implementing electric propulsion systems. Progress on current hardware development, recent test activities and future plans are discussed.

Pencil, Eric J.↗

DOE OSTI2016

SU-F-E-03: PET/CT Guided Dose Boost to Hypoxic Sub-Volume in Nasopharyngeal Carcinomas Using Self-Optimizing Non-Uniform VMAT

Purpose: This study is to evaluate the feasibility of simultaneously integrated boost (SIB) to hypoxic subvolume (HTV) in nasopharyngeal carcinomas under the guidance of 18F-Fluoromisonidazole (FMISO) PET/CT using a novel non-uniform volumetric modulated arc therapy (VMAT)technique. Methods: Eight nasopharyngeal carcinoma patients treated with conventional uniform VMAT were retrospectively analyzed. For each treatment, actual conventional uniform VMAT plan with two or more arcs (2–2.5 arcs, totally rotating angle < 1000o) was designed with dose boost to hopxic subvolume (total dose, 84Gy) in the gross tumor volme (GTV) under the guidance of 18F- FMISO PET/CT. Based on the same dataset, experimental single arc non-uniform VAMT plans were generated with the same dose prescription using customized software tools. Dosimetric parameters, quality assurance and the efficiency of the treatment delivery were compared between the uniform and non-uniform VMAT plans. Results: To develop the non-uniform VMAT technique, a specific optimization model was successfully established. Both techniques generate high-quality plans with pass rate (>98%) with the 3mm, 3% criterion. HTV received dose of 84.1±0.75Gy and 84.1±1.2Gy from uniform and non-uniform VMAT plans, respectively. In terms of target coverage and dose homogeneity, there was no significant statistical difference between actual and experimental plans for each case. However, for critical organs at risk (OAR), including the parotids, oral cavity and larynx, dosimetric difference was significant with better dose sparing form experimental plans. Regarding plan implementation efficiency, the average machine time was 3.5 minutes for the actual VMAT plans and 3.7 minutes for the experimental nonuniform VMAT plans (p>0.050). Conclusion: Compared to conventional VMAT technique, the proposed non-uniform VMAT technique has the potential to produce efficient and safe treatment plans, especially in cases with complicated anatomical structures and demanding dose boost to subvolumes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2019

Prototyping the BOPTEST Framework for Simulation-Based Testing of Advanced Control Strategies in Buildings

Advanced control strategies are becoming increasingly necessary in buildings in order to meet and balance requirements for energy efficiency, demand flexibility, and occupant comfort. Additional development and widespread adoption of emerging control strategies, however, ultimately require low implementation costs to reduce payback period and verified performance to gain control vendor, building owner, and operator trust. This is difficult in an already first-cost driven and risk-averse industry. Recent innovations in building simulation can significantly aid in meeting these requirements and spurring innovation at early stages of development by evaluating performance, comparing state-of-the-art to new strategies, providing installation experience, and testing controller implementations. This paper presents the development of a simulation framework consisting of test cases and software platform for the testing of advanced control strategies (BOPTEST - Building Optimization Performance Test). The objectives and requirements of the framework, components of a test case, and proposed software platform architecture are described, and the framework is demonstrated with a prototype implementation and example test case.

Blum, David↗

DOE OSTI2020

Dragonstone Strategy – State of Cybersecurity in the Oil & Natural Gas Sector

The oil & natural gas (ONG) system touches every corner of the nation and increased communications & control capabilities have not only allowed for greater efficiency of system operation, but have also created a massive target for adversaries to launch cyber-attacks. Like any other heavy industrial process, the ONG system relies on a complex system of information technology (IT) and operational technology (OT) devices. The current state of cyber-preparedness across the ONG industry varies from organization to organization. Among the most common challenges that ONG companies face are remote locations, longlived field assets, and lacking capabilities to find and track malware on their systems. ONG companies tend to be concerned with lack of cyber-awareness from employees, risk stemming from remote access for operations & maintenance, and software vulnerabilities within third-party equipment. Various industry and government organizations are performing research and development activities to address some of these challenges, but in many cases industry stakeholders are not aware of solutions that already exist. It is clear that a need exists for a coherent, comprehensive, multi-layered strategy for assuring the security and resilience of the nation's pipeline infrastructure against cyber threats. For a variety of reasons, the general consensus from stakeholders interviewed by LLNL is that the state of cyber-security within the electric grid is currently outpacing its ONG cousin. Existing strategies for the resilience and cyber-security of the electric grid can and should be leveraged to provide immediate benefits to the ONG system. In LLNL’s view, there are two key factors currently limiting the development of necessary cyber-practices within the ONG industry: The sheer number of differing regulatory bodies and trade groups offering both standards and best-practice recommendations for ONG cyber-security makes it difficult to create a comprehensive, directed, and coherent strategy that is applicable to all players within the ONG industry. The ONG industry is unaware of potentially useful technologies that have been developed for ensuring cyber-security of other infrastructure systems, such as the electric grid. Leveraging these technologies—and the science and engineering behind them—can provide some low-hanging fruit that can greatly improve cyber-security in the ONG industry without significant investments in terms of time and money. In the months following this report, LLNL will continue to perform outreach to key oil & gas industry stakeholders in a continual effort to identify the most pressing cyber-resilience issues in the industry. This outreach will be supplemented with LLNL’s threat intelligence capabilities to begin painting a clearer picture of the overall threat landscape faced by this sector. This assessment will be threat-informed and while the strategy itself will not be classified we will leverage intelligence analysis and adversary capabilities to identify gaps in current cybersecurity practices for oil & gas pipeline systems. Recommended efforts will be compiled into a cyber-resilience roadmap for the oil & gas pipeline sector, in which LLNL will highlight priority activities to immediately improve the state of cyber-resilience in the industry.

02 PETROLEUM↗

DOE OSTI2015

Postclosure assessment modelling of a deep geologic repository for low and intermediate level radioactive waste in Ontario, Canada - 15145

In 2011, Ontario Power Generation (OPG) submitted an Environmental Impact Statement and a Preliminary Safety Report (PSR) to the federal authorities in Canada to support an application for a site preparation and construction licence for a Deep Geologic Repository (DGR) for low and intermediate level radioactive waste (L and ILW). The DGR, which is proposed to be located close to the existing Western Waste Management Facility (WWMF) at the Bruce nuclear site, would receive L and ILW arising from the operation and refurbishment of OPG's nuclear reactors; the wastes are currently stored safely at the WWMF. The PSR is supported by postclosure safety assessment modelling, including a total-systems level model implemented in the AMBER compartment modelling software that draws directly on detailed groundwater and coupled groundwater and gas modelling using the FRA3DVS-OPG and TOUGH2 codes. A full suite of calculation cases is managed within a single AMBER model, which aided efficient management of the calculation files and quality assurance. Assessment of expected/normal evolution cases results in maximum calculated effective doses to humans that are more than five orders of magnitude below associated criteria. Assessment of conservative disruptive and 'what if' scenarios results in maximum calculated doses that are higher than those for the normal evolution cases, but which, when the low likelihood of occurrence is taken into account, remain significantly below the associated risk criterion. The assessment demonstrates that deep geologic repositories can provide a safe disposal option and provides an example of evaluating the safety of projects on long time scales. It shows how results from detailed groundwater and gas codes can be incorporated into assessment-level codes such as AMBER, thereby providing a single systems model that can be used to efficiently evaluate a wide range of scenarios and associated calculation cases. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗