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At least 199 records · Page 11

Distributed Computing Framework for Synthetic Radar Application

We are developing an extensible software framework, in response to Air Force and NASA needs for distributed computing facilities for a variety of radar applications. The objective of this work is to develop a Python based software framework, that is the framework elements of the middleware that allows developers to control processing flow on a grid in a distributed computing environment. Framework architectures to date allow developers to connect processing functions together as interchangeable objects, thereby allowing a data flow graph to be devised for a specific problem to be solved. The Pyre framework, developed at the California Institute of Technology (Caltech), and now being used as the basis for next-generation radar processing at JPL, is a Python-based software framework. We have extended the Pyre framework to include new facilities to deploy processing components as services, including components that monitor and assess the state of the distributed network for eventual real-time control of grid resources.

synthetic aperture radar (SAR)↗

Strategic Framework for NASA’s Space Technology Mission Directorate

In October 2016, NASA’s Space Technology Mission Directorate (STMD) began adopting a new strategic framework that focuses investment prioritization and communication on impacts, outcomes, and challenges. The structure of the framework has been modeled after one successfully pioneered by NASA’s Aeronautics Research Mission Directorate over the past five years, incorporating lessons learned and changes where appropriate. The Framework is driven by two major factors: (a) dialogue with the community and (b) analysis of the overarching trends shaping the course of civilian space research. These factors are captured in the Framework as Mega-Drivers, which represent major axes of change within the space industry and are characterized by a collection of industry trends and projections. In response to these Mega-Drivers, STMD has developed its understanding of the vision for the future of civilian space relative to STMD space research, captured in five Strategic Thrusts that represent the major lines of investment within STMD’s portfolio. Within each of these Strategic Thrusts, multiple measureable, community-level goals have been established that STMD chooses to pursue as part of a joint effort across the community. STMD chose these goals based upon their potential impact, refers to them as Outcomes within the Framework. These Outcomes are decomposed into the products and/or capabilities that will be delivered by STMD, represented in the framework as Technical Challenges. This paper will further describe the framework structure and the progress that has been in defining each of the above elements to date.

Earle, Kevin D.↗

Strategic Framework for NASA’s Space Technology Mission Directorate

In October 2016, NASA’s Space Technology Mission Directorate (STMD) began adopting a new strategic framework that focuses investment prioritization and communication on impacts, outcomes, and challenges. The structure of the framework has been modeled after one successfully pioneered by NASA’s Aeronautics Research Mission Directorate over the past five years, incorporating lessons learned and changes where appropriate. The Framework is driven by two major factors: (a) dialogue with the community and (b) analysis of the overarching trends shaping the course of civilian space research. These factors are captured in the Framework as Mega-Drivers, which represent major axes of change within the space industry and are characterized by a collection of industry trends and projections. In response to these Mega-Drivers, STMD has developed its understanding of the vision for the future of civilian space relative to STMD space research, captured in five Strategic Thrusts that represent the major lines of investment within STMD’s portfolio. Within each of these Strategic Thrusts, multiple measurable, community-level goals have been established that STMD chooses to pursue as part of a joint effort across the community. STMD chose these goals based upon their potential impact, refers to them as Outcomes within the Framework. These outcomes are decomposed into the products and/or capabilities that will be delivered by STMD, represented in the framework as Technical Challenges. This paper will further describe the framework structure and the progress that has been in defining each of the above elements to date.

Kevin D Earle↗

Framework for Estimating Performance and Associated Uncertainty for Modified Aircraft Configurations

Flight testing has been the historical standard for determining aircraft airworthiness - however, increases in the cost of flight testing and the accuracy of inexpensive CFD promote certification by analysis to reduce or replace flight testing. A framework is introduced to predict the performance in the special case of a modification to an existing, previously certified aircraft. This framework uses a combination of existing flight test or high fidelity data of the original aircraft as well as lower fidelity data of the original and modified configurations. Two methods are presented which estimate the model form uncertainty of the modified configuration, which is then used to conduct non-deterministic simulations. The framework is applied to an example aircraft system with simulated flight test data to demonstrate the ability to predict the performance and associated uncertainty of modified aircraft configurations. However, it is important that the models and methods used are applicable and accurate throughout the intended use domain. The factors and limitations of the framework are explored to determine the range of applicability of the framework. The effects of these factors on the performance and uncertainty results are demonstrated using the example aircraft system. The framework is then applied to NASA’s X-57 Maxwell and each of its modifications. The estimated performance and associated uncertainties are then compared to the airworthiness criteria to evaluate the potential of the framework as a component to the certification by analysis process.

Uncertainty Quantification↗

Truncating 2D Framework Materials Down to a Single Pore: Synthetic Approaches and Opportunities

Here, in this Accounts article, we summarize our recent work on truncating conjugated two-dimensional framework materials down to a single pore, or a single macrocycle. Conjugated 2D architectures have emerged as one of the most synthetically adaptable motifs for coupling semiconductivity and porosity in metal–organic frameworks (MOFs) and covalent organic frameworks (COFs). However, despite their prevalence, 2D architectures have several limitations. In particular, the strong interlayer π–π stacking can limit both processability and the accessibility of internal active sites. We have found that simple macrocycles preserve key aspects of 2D framework structure and function, including porosity and out-of-plane electrical conductivity, while providing improved processability, surface tunability, and mass transport properties. In this article, we first describe our synthetic approach and general design considerations. Specifically, we show how ditopic analogues of the tritopic ligands commonly found in the synthesis of 2D MOFs and COFs can be used to achieve a diverse library of conjugated macrocycles that resemble fragments of semiconducting frameworks in both form and function. The length of the peripheral side chains, the size of the aromatic core, and the solubility of intermediates are all key variables in favoring selective macrocycle formation over undesired linear polymers and oligomers. Next, we highlight the unique advantages that macrocycles provide, including improved processability, atomically precise surface tunability, and greater active site accessibility. In particular, the identity of the peripheral side chains dramatically impacts both solubility and colloidal stability as well as crystal size and morphology. We further show how the solution processability and nanoscale dimensions of macrocycles can simplify electronic device fabrication and improve electrochemical performance. Finally, we end with a forward-looking discussion on how macrocycles offer a unique bridge between conjugated molecules and extended frameworks, enabling new application areas and fundamental science.

charge transport↗

Nanoporous weakly coordinating anionic frameworks (Final Technical Report)

Under this award, we synthesized and characterized new weakly coordinating, anionic covalent organic frameworks. The motivation was to expand the class of covalent organic frameworks though the introduction of the first weakly coordinating anionic ones. The significance of the weakly coordinating anionic character of these frameworks is associated with the character of the counter (metal) cations in their pores. Those counter-cations, due to the inability to effectively coordinate to the pore walls, have a “naked”, and thus highly electrophilic, Lewis acidic character. Such properties are expected to translate to a number of interesting physical properties that can be potentially used for a range of energy-relevant applications. One of these applications is gas adsorption, separation, and storage. The electrophilic, Lewis acidic character of the counter-cations are expected to strongly bind to gas molecules entering the pores leading to higher gas sorption capacities. Other applications include heterogeneous catalysis, ion exchange, and solid state ion conduction. Within the project we explored a range of chemical blocks, and tested synthesis conditions to polymerize these building blocks to form the target materials. In particular, we focused on materials with group 15 elements like phosphorus in the oxidation state +5 and the coordination number 6, that have a formal -1 charge. The synthesis of such materials is challenging because its success depends on the absence of residual monomeric and oligomeric side-products in the pores, and the absence of significant framework interpenetration. Crystalline forms of these materials require sufficient reversibility of the polymerization reaction (which is difficult to achieve because group 15 elements like P tend to make strong covalent bonds with neighbored elements), as well as suitable polymerization rates that prevent the formation of kinetically controlled products. We had success with the preparation of anionic porous organic frameworks with anionic building blocks containing P(V)O6 octahedra synthesized through Yamamoto coupling reactions. These materials are non-crystalline because of the irreversible nature of the Yamamoto coupling reaction, but show porosity. The porosity and surface area can be significantly increased by co-reaction with electrostatically neutral co-reactants. Very high porosity and surface areas can be achieved when the materials are washed with hydrochloric acid. This method is commonly used to free products from Yamamoto coupling reactions from by-products. Indeed, this method removed by products from the pores of our materials, however it also led to the hydrolysis of the PO6 octahedra to form pending phosphonic acid groups (-PO3H)-groups in the frameworks (PA-POFs) which was actually not desired. Nonetheless, these materials showed high CO2 sorption capacities. In addition, they show extremely high (actually record) sorption capacities for the removal of a range of common micropollutants such as bisphenol A (BPA) and 4-nitrophenol in water. BPA is a wide-spread organic pollutant and a known endocrine disruptor. The maximum adsorption capacity of BPA at equilibrium is found to be as high as 3,366 mg g-1 by Langmuir adsorption model, which is more than 10 times greater than peer materials. The polymer also rapidly removes various other organic micropollutants with more than 90% removal efficiencies. In addition, the PA-POF material can be regenerated at least five times by mild washing using methanol without significant loss in removal efficiency. This is significant advantage over commonly used activated carbon materials (that are in Brita water faucet filters, for example). Comparison studies showed that only materials with the phosphonate groups show extreme sorption although the number of PA group is actually small according to solid state NMR and EDX data. More research would be needed to investigate why this is (a possibility is that the phosphonate groups have a multiplying effect in which a PA-induced initial adsorption leads to the adsorption of much more adsorbate). The extreme sorption capabilities can also be visually seen when colored adsorbates such as 4-nitrophenol are used, as the adsorption of the nitrobenzene leads to the decoloration of the solution. We have produced three short videos that illustrate the sorption capabilities compared to two peer materials (activated carbon from dismantled Brita water filters, and a electrostatically neutral, chemically related, porous organic polymer, respectively).

36 MATERIALS SCIENCE↗

Evaluating energy justice metrics in early-stage science and technology research using the JUST-R metrics framework

Embedding principles of energy justice throughout all aspects of clean energy technology research and development (R&D) can facilitate a more just energy transition; yet gaps remain in our understanding of how to best integrate energy justice from the earliest R&D stages. The Justice Underpinning Science and Technology Research (JUST-R) metrics framework has been developed to enable early-stage energy researchers to assess and address justice considerations associated with their research, but the impacts of the framework, and others like it, have yet to be evaluated. This study seeks to evaluate the JUST-R metrics framework in terms of its effectiveness and appeal to researchers engaged in early-stage technical R&D using qualitative analyses of documents and workshop transcripts. We find that the metrics framework helps researchers identify problems and potential solutions surrounding the energy justice implications of their work and spurs a change in perspective for researchers, but, simultaneously, there is no evidence of solution follow-through within the evaluation timeframe. Greater institutional support, specialization to research areas, knowledge of energy justice fundamentals, and earlier incorporation of energy justice considerations in research projects arise as factors needed to aid continued use of the framework and pursuit of identified solutions. This evaluation protocol and these findings can serve as a guide for improving other frameworks with similar goals of encouraging sociotechnical engagement in early-stage energy R&D.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Optimal sizing of battery energy storage systems for peak shaving and demand response using a degradation-aware Bayesian Optimization-Mixed-Integer Linear Programming framework

The increasing integration of renewable energy and rising electricity demand highlight the importance of battery energy storage systems for peak shaving and demand response. Unlike prior approaches that overlook operational impacts on degradation, this study proposes a Bayesian Optimization–Mixed Integer Linear Programming framework for optimal battery energy storage system sizing. In this framework, Mixed Integer Linear Programming determines short-term scheduling while a calibrated electrochemical model iteratively evaluates degradation. The central hypothesis is that the framework can efficiently identify optimal sizes that yield realistic and economically robust outcomes. The method is tested across three scenarios: peak shaving, peak shaving with energy-reduction demand response, and peak shaving with power-reduction demand response. Results show that the framework converge to the optimum within 20 iterations out of 150 possible sizes. Under baseline conditions, the framework consistently selects the smallest feasible system, minimizing unnecessary degradation costs from oversized storage. Sensitivity analyses reveal that larger systems are favored as demand rates or incentives increase. Comparisons of demand response programs indicate that power-reduction demand response offers greater economic benefits than energy-reduction demand response, although demand savings from peak shaving remain the dominant contributor to overall performance. This study demonstrates that the proposed framework balances computational tractability with degradation fidelity, identifies critical economic thresholds for investment, and offers a practical, flexible tool to guide industrial stakeholders in cost-effective battery energy storage system deployment.

Batteries↗

Optimizing district energy systems by integrating Borehole Thermal Energy Storage Using a Mixed-Integer Linear Programming g-function framework with a Multi-Timescale Rolling Horizon method

Shallow geothermal has gained increasing attention in recent years; however, a reliable framework for its accurate incorporation into large-scale energy system optimization remains lacking. This study proposes a Mixed-Integer Linear Programming (MILP) framework combined with the g-function approach to integrate Borehole Thermal Energy Storage (BTES) technology into energy system optimization. Validation against a Modelica-based reservoir network simulation demonstrates that the proposed framework effectively captures the ground thermal response under varying energy loads and accurately estimates the borefield energy supply. To enhance scalability, a Rolling Horizon with Multi-Timescale (RH-MTS) method is further introduced, reducing computational time by 73 % for the 1-year optimization model with only minor loss of optimality. The framework is demonstrated through the case study of the UC Berkeley campus. Results indicate that BTES is a cost-effective and low-carbon solution: two borefields comprising 382 boreholes can meet 8.0 % and 6.6 % of the total campus heating and cooling demand, respectively, at an average energy rate of 0.70–0.77 USD/kWh and carbon intensity of 0.54 kg-CO2/kWh. Short-term analysis reveals a 35%–65% decline in BTES energy flow after 3–6 months of continuous heating/cooling operation, while long-term simulation shows that annual energy production of BTES can vary by up to 12.0 % after four years before stabilizing. Overall, this study develops a novel optimization framework that couples physics-based g-function method with MILP optimization framework, thereby advancing methodological development for shallow-geothermal integration and providing actionable guidance for BTES deployment in district-energy systems.

Yang, Jiahui↗

Cybersecurity Vulnerability Mitigation Framework through Empirical Paradigm: Enhanced Prioritized Gap Analysis

Existing cybersecurity vulnerability assessment tools were designed based on the policies and standards defined by organizations such as the U.S. Department of Energy and the National Institute of Standards and Technology (NIST). Frameworks such as the cybersecurity capability maturity model (C2M2) and the NIST Cybersecurity Framework (CSF) are often used by the critical infrastructure owners and operators to determine the cybersecurity maturity of their facility. Although these frameworks are exceptional at performing qualitative cybersecurity analysis and identifying vulnerabilities, they do not provide a means to perform prioritized mitigation of those vulnerabilities in order to achieve a desired cybersecurity maturity. To address that challenge, we developed a framework and software application called the cybersecurity vulnerability mitigation framework through empirical paradigm (CyFEr). This paper presents the detailed architecture of CyFEr’s enhanced prioritized gap analysis (EPGA) methodology and its application to CSF. The efficacy of the presented framework is demonstrated by comparing against existing similar models and testing against the cyber injects from a real-world cyber-attack that targeted industrial control systems (ICS) in critical infrastructures.

Gourisetti, Sri Nikhil G.↗

Liquid and Glass Phases of an Alkylguanidinium Sulfonate Hydrogen-Bonded Organic Framework

Glassy phases of framework materials feature unique and tunable properties that are advantageous for gas separation membranes, solid electrolytes, and phase-change memory applications. However, the structural and chemical diversity of porous frameworks that can be liquified and quenched into a glass has been limited by thermal decomposition at-or below-the high temperatures required to induce a melting transition. Utilizing a desymmetrization strategy, in this work we report a new guanidinium organosulfonate hydrogen-bonded organic framework (HOF) that melts and vitrifies below 100 °C. In this low-temperature regime, non-covalent interactions between guest molecules and the porous framework become a dominant contributor to the overall stability of the structure, resulting in unusual phase behavior such as guest dependent melting, glass, and recrystallization transitions. Through molecular dynamics simulations and pair distribution function analysis, we show that the local structure of the amorphous liquid and glass phase resembles that of the parent crystalline framework. Access to molten phases of framework materials at moderate temperatures should permit the use of more thermally sensitive functional groups and enhance the structural control and tunability that can be realized in network-forming glasses.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Structural and electronic switching of a single crystal 2D metal-organic framework prepared by chemical vapor deposition

The incorporation of metal-organic frameworks into advanced devices remains a desirable goal, but progress is hindered by difficulties in preparing large crystalline metal-organic framework films with suitable electronic performance. We demonstrate the direct growth of large-area, high quality, and phase pure single metal-organic framework crystals through chemical vapor deposition of a dimolybdenum paddlewheel precursor, Mo 2 (INA) 4 . These exceptionally uniform, high quality crystals cover areas up to 8600 µm 2 and can be grown down to thicknesses of 30 nm. Moreover, scanning tunneling microscopy indicates that the Mo 2 (INA) 4 clusters assemble into a two-dimensional, single-layer framework. Devices are readily fabricated from single vapor-phase grown crystals and exhibit reversible 8-fold changes in conductivity upon illumination at modest powers. Moreover, we identify vapor-induced single crystal transitions that are reversible and responsible for 30-fold changes in conductivity of the metal-organic framework as monitored by in situ device measurements. Gas-phase methods, including chemical vapor deposition, show broader promise for the preparation of high-quality molecular frameworks, and may enable their integration into devices, including detectors and actuators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

GAHLS: an optimized graph analytics based high level synthesis framework

The urgent need for low latency, high-compute and low power on-board intelligence in autonomous systems, cyber-physical systems, robotics, edge computing, evolvable computing, and complex data science calls for determining the optimal amount and type of specialized hardware together with reconfigurability capabilities. With these goals in mind, we propose a novel comprehensive graph analytics based high level synthesis (GAHLS) framework that efficiently analyzes complex high level programs through a combined compiler-based approach and graph theoretic optimization and synthesizes them into message passing domain-specific accelerators. This GAHLS framework first constructs a compiler-assisted dependency graph (CaDG) from low level virtual machine (LLVM) intermediate representation (IR) of high level programs and converts it into a hardware friendly description representation. Next, the GAHLS framework performs a memory design space exploration while account for the identified computational properties from the CaDG and optimizing the system performance for higher bandwidth. The GAHLS framework also performs a robust optimization to identify the CaDG subgraphs with similar computational structures and aggregate them into intelligent processing clusters in order to optimize the usage of underlying hardware resources. Finally, the GAHLS framework synthesizes this compressed specialized CaDG into processing elements while optimizing the system performance and area metrics. Evaluations of the GAHLS framework on several real-life applications (e.g., deep learning, brain machine interfaces) demonstrate that it provides 14.27× performance improvements compared to state-of-the-art approaches such as LegUp 6.2.

97 MATHEMATICS AND COMPUTING↗

Promotion of adsorptive and catalytic properties of zeolitic Brønsted acid sites by proximal extra-framework Si(OH) x groups

Steric confinement in zeolites influences the catalytic conversion of alkanes. For zeolitic Brønsted acid sites, proximate extra-framework species introduce additional confinement to the pore constraints, enhancing the catalytic activity of alkane cracking. Although extra-framework alumina has been the most studied, here we report the element-specific impact of silica species. Further, by grafting extra-framework silica species close to Brønsted acid sites in H-ZSM-5 zeolite, the binding of bases like pyridine and amines is strengthened via van der Waals interactions with their aryl or alkyl chains. Brønsted acid sites close to extra-framework silica achieve a higher reaction rate of protolytic cracking of n-pentane via enthalpic (unlike entropic, as with extra-framework alumina) stabilization of the transition state by 24–51 kJ mol −1 . The lower activation energy points to an earlier transition state than in the presence of extra-framework alumina, with a better stabilization of the carbonium ions in the transition state compared to the parent zeolite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A Secondary Control Framework for Microgrid Interoperability With Vendor-Agnostic Grid-Forming Units: Design, Implementation, and Demonstration via Large-Scale Hardware Setup

The reliable operation of islanded microgrids increasingly depends on secondary controls that restore voltage and frequency to nominal values and ensure accurate active and reactive power sharing. Centralized secondary control architectures achieve high accuracy through global coordination at the cost of single-point failures and limited scalability compared with decentralized/distributed approaches. But a critical gap remains in addressing the interoperability and vendor-agnostic operation of secondary controls in real-world microgrids where heterogeneous diesel generator(s) and grid-forming (GFM) inverter(s) from multiple manufacturers always coexist. Practical and vendor-agnostic interoperability guidelines for the secondary control architecture of microgrids with multiple GFM units have not yet been developed; therefore, this paper proposes an interoperable and vendor-agnostic secondary control framework that operates seamlessly across GFM units from different vendors without relying on proprietary controls and protocols, hardware, or lock-ins. The framework leverages existing communication infrastructures (e.g., Modbus TCP/IP) to enable cost-effective deployment while addressing practical challenges, such as packet loss and quantization errors. Mitigation strategies-including data averaging, situational event-triggered control, and finite-iteration execution-are introduced to enhance reliability under real-world conditions. A generalized modeling and design framework is also presented, supported by robustness analysis to demonstrate independence from vendor-specific implementations. The proposed framework is validated through a large-scale hardware demonstration using a 3-$\phi$, 480-V, 60-Hz, 713-kVA laboratory hardware microgrid involving a heterogeneous diesel generator and multiple GFM inverters, showcasing its effectiveness in achieving stable voltage and frequency restoration and accurate power sharing under practical constraints. The results highlight the framework's potential as a scalable and practical solution for next-generation microgrids requiring openness, standard framework, and interoperability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Validation of Microgrid Algorithms using At-Scale Simulation and Emulation Real-Time (ASSERT) Framework

This paper presents a novel framework for validating microgrid algorithms using a At-Scale Simulation and Emulation Real-Time (ASSERT) setup. The proposed universal microgrid validation framework was developed at Advanced Research on Integrated Energy Systems (ARIES) platform at National Renewable Energy Laboratory in Golden, Colorado, USA. As the number of intercommunicating devices grow in power systems, along with more integration of inverter-based resources, developing and validating microgrid operation and control algorithms is becoming complex and time-consuming task. The ASSERT framework is designed to provide a comprehensive, accurate, and efficient solution for validating microgrid algorithms. It combines at-scale simulations and real-time emulation to create a virtual environment that closely mimics the behavior of a physical microgrids which are characteristic of future smart distribution systems, such as: (1) increasing variability in the physical size of new energy technologies; (2) requiring control large numbers of interconnected devices, and (3) integrating diverse technologies that have not previously worked together. The paper describes the technical details of the ASSERT framework, its validation process, and its benefits over traditional validation methods. The framework's ability to validate the performance of various algorithms is demonstrated through a case study, which shows that it can effectively identify the weaknesses of an algorithm and optimize its performance. Overall, the ASSERT framework is a promising tool that can significantly enhance the development and validation of microgrid algorithms, leading to more reliable and efficient microgrid operation.

at-scale↗

Hybrid Data-Driven Physics-Based Model Framework Implementation: Towards a Secure Cyber-Physical Operation of the Smart Grid

False data injection cyber-attack detection models on smart grid operation have been much explored recently, considering analytical physics-based and data-driven solutions. Recently, a hybrid data-driven physics-based model framework for monitoring the smart grid is developed. However, the framework has not been implemented in real-time environment yet. In this paper, the framework of the hybrid model is developed within a real-time simulation environment. OPAL-RT real-time simulator is used to enable Hardware-in-the-Loop testing of the framework. IEEE 9-bus system is considered as a testing grid for gaining insight. The process of building the framework and the challenges faced during development are presented. The performance of the framework is investigated under various false data injection attacks.

false data injection attack, machine learning, sta↗

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks. In particular, the eye is a signature feature of a mature TC. Therefore, knowing the eyes’ locations and movements is crucial for both operational weather forecasts and climate risk assessments. Recently, a multilevel robustness framework has been introduced to study the critical points of time-varying vector fields. The framework quantifies the robustness (i.e., structural stability) of critical points across varying neighborhoods. By relating the multilevel robustness with critical point tracking, the framework has demonstrated its potential in cyclone tracking. An advantage is that it identifies cyclonic features using only 2D wind vector fields, which is encouraging as most tracking algorithms require multiple dynamic and thermodynamic variables at different altitudes. A disadvantage is that the framework does not scale well computationally for datasets containing a large number of cyclones. Herein this paper introduces a topologically robust physics-informed tracking framework (TROPHY) for TC tracking. The main idea is to integrate physical knowledge of TC to drastically improve the computational efficiency of multilevel robustness framework for large-scale climate datasets. First, during preprocessing, we propose a physics-informed feature selection strategy to filter 90% of critical points that are short-lived and have low stability, thus preserving good candidates for TC tracking. Second, during in-processing, we impose constraints during the multilevel robustness computation to focus only on physics-informed neighborhoods of TCs. We apply TROPHY to 30 years of 2D wind fields from reanalysis data in ERA5 and generate a number of TC tracks. In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics (e.g., frequency, intensity, duration, latitudes with maximum intensity, and genesis) that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.

97 MATHEMATICS AND COMPUTING↗