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NASA NTRSDate not supplied

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

The field of prognostics and health management provides quantitative methods for monitoring and predicting the health of physical systems. Prognostics algorithms are useful in that they can be employed to assess the current state of a system, propagate the system state throughout time, and predict potential anomalies or failures that may occur. However, effective prognosis can be challenging to achieve in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for some prognostics applications. In this work, we implement three new algorithmic approaches to prediction (sampling methods, variable prediction time step, variable prediction sample size) with the goal of improving computational efficiency while minimizing decrease in model accuracy. To quantitatively analyze our results, we examine a use-case of degradation of a Lithium-ion battery. Notably, through this work it was found that none of the sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. However, our results show that prediction accuracy is highly dependent on the time step used, and that an appropriate time step can optimize both model accuracy and simulation efficiency. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment in an application-specific manner may prove useful in some applications. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency of prognosis.

Prognostics↗

NASA NTRSDate not supplied

Aqueous Alteration on the Ryugu Parent Body Constrained by Chemical Equilibrium Models

The composition of solid samples returned from the asteroid 162173 Ryugu byHayabusa2 indicates aqueous alteration of rocks that formed a parent body of Ryugu [1, 2]. As on parent bodies of carbonaceous chondrites [3-5], Ryugu materials could have went through (1) accretion of anhydrous and reduced rocky grains together with water-rich ices, (2) melting of ices in the body’s interior through release of radiogenic heat [6], and (3)aqueous alteration of rocky and organic materials that produced secondary minerals, salt- and organic-bearing water solutions, gases, and altered organic matter. Although the bulk chemical composition and major mineralogy (phyllosilicates, magnetite, pyrrhotite, carbonates, phosphates, etc.) of Ryugu [1,2]are similar to those of CI carbonaceous chondrites [3-5, 7], the lack of sulfates and a deficiency of oxygen in the returned samples suggest a distinct alteration pathway. Chondritic materials [3-5] do not indicate complete chemical equilibration though low-temperature parent body processes. However, calculations of chemical equilibria in modeling rock-water-gas type systems[e.g., 8, 9], could assess deviations of chondritic materials from equilibrium conditions and constrain partitioning of chemical elements between solid, aqueous, and gas phase for different stages of alteration. Here we constrained speciation of solid, aqueous, and gaseous phases during aqueous alteration on the Ryugu parent body through chemical equilibrium calculations.

M Yu Zolotov↗

NASA NTRS2022

Simons Observatory: Constraining inflationary gravitational waves with multitracer B-mode delensing

We introduce and validate a delensing framework for the Simons Observatory (SO), which will be used to improve constraints on inflationary gravitational waves by reducing the lensing noise in measurements of the B modes in CMB polarization. SO will initially observe CMB by using three small aperture telescopes and one large-aperture telescope. While polarization maps from small-aperture telescopes will be used to constrain inflationary gravitational waves, the internal CMB lensing maps used to delens will be reconstructed from data from the large-aperture telescope. Since lensing maps obtained from the SO data will be noise dominated on subdegree scales, the SO lensing framework constructs a template for lensing-induced B modes by combining internal CMB lensing maps with maps of the cosmic infrared background from Planck as well as galaxy density maps from the LSST survey. We construct a likelihood for constraining the tensor-to-scalar ratio r that contains auto and cross spectra between observed B modes and the lensing B-mode template. We test our delensing analysis pipeline on map-based simulations containing survey nonidealities, but that, for this initial exploration, does not include contamination from Galactic and extragalactic foregrounds. We find that the SO survey masking and inhomogeneous and atmospheric noise have very little impact on the delensing performance, and the r constraint becomes σ(r)≈0.0015 which is close to that obtained from the idealized forecasts in the absence of the Galactic foreground and is nearly a factor of 2 tighter than without delensing. We also find that uncertainties in the external large-scale structure tracers used in our multitracer delensing pipeline lead to bias much smaller than the 1σ statistical uncertainties.

Toshiya Namikawa↗

NASA NTRSDate not supplied

Constraining the Hydration of X-Ray Amorphous and Clay Mineral Phases in Gale Crater, Mars

Clay minerals and salts in the Gale crater stratigraphy investigated by the Mars Science Laboratory (MSL) Curiosity rover preserve information about sediment sources, depositional environment, and post-depositional alteration history. The compositions of amorphous components in samples have bearing on the redox potential, pH, and chemistry of alteration fluids, and on the heterogeneity of these conditions. Interlayer clay hydration in present-day Gale crater could be an indication of high water/rock ratios of late-stage fluid alteration events, which increases the potential habitability of these post-depositional environments. The MSL Dynamic Albedo of Neutrons instrument (DAN) measures bulk hydration and here we attempt to determine the hydration states of both clay minerals and amorphous components throughout the Curiosity traverse to constrain the abundance of individual amorphous phases and determine if clay interlayer water is present today. These implications are also more broadly applicable to similar sedimentary successions outside Gale crater. In this study, we compare hydration results from DAN to mineralogical results from the MSL Chemistry and Mineralogy instrument (CheMin) for 16 different fluvio-lacustrine sample locations. These samples typically contain one or more hydrated crystalline phases, a hydrated X-ray amorphous fraction composed of multiple amorphous phases, and one or more clay mineral phases which CheMin has consistently measured as collapsed (i.e., no interlayer water). However, Gale samples are known to dehydrate during sample acquisition and handling, and because DAN measures hydration to a depth of tens of cm, we can test for the presence of clay interlayer water in situ by comparing DAN bulk hydration to CheMin mineralogy. We can also constrain the hydration of the samples’ amorphous fractions, and with geochemical data from the ChemCam and APXS instruments, this will allow us to better define the phases which compose this fraction.

S Czarnecki↗

NASA NTRS2024

Under-Constrained SEE Data: Implications for Estimating and Bounding SEE Rates

Increasingly scarce SEE testing resources and rapid growth of the New Space sector have increased the prevalence of under-constrained SEE data. We develop Monte Carlo tools to assess implications for SEE rate estimation. We also show that Bayesian Priors based on large datasets of SEL susceptible parts can augment under-constrained data and improve bounds on SEL rates. The resulting Bayesian Priors are also useful for bounding system SEL risk.

Single-event effect↗

NASA NTRSDate not supplied

Habitability Potential of Martian Hydrothermal Systems Constrained from Exploration of a Magma-Sediment Hydrothermal System in the Colorado Plateau

Mars has a crust predominately composed of basalt, which displays wide-spread processes including volcanic hydrothermal systems and reference within. There is an abundance of evidence of previous low temperature hydrous alteration; however, finding evidence of high-temperature hydrothermal activity has been challenging. Therefore, we are investigating a mafic dike and the surrounding metamorphic contact zone to constrain how to find such systems on Mars and their habitability potential on Earth and by extension Mars. DC Dike (DCD) is in the Colorado Plateau, in south-central Utah, and intruded the Entrada formation Sandstone between 3.8 and 4.6 Ma. We chose Mars analog instrumentation to make our results directly applicable to those on Mars: Visible-Near Infrared reflectance spectroscopy (VNIR), X-Ray Diffraction (XRD), and Scanning Electron Microscope (SEM). 21 samples were analyzed with an Ore Express VNIR with wavelengths from 350-2500 nm. Bulk mineralogy is determined by using a Panalytical XRD including for clay fraction and soil separation analysis. Finally, samples are prepped as thin sections and will be analyzed using a SEM. All these techniques will be used to constrain: the mineralogy of the system, how the hydrothermal system cooled, the habitability of the cooling system, and how DCD relates to similar dikes in the area and on Mars. All of these results will then be compared to similar systems Mars, and if they too could have been habitable environments.

R. A. Slank↗

NASA NTRS2023

Single-Scattering Properties of Ellipsoidal Dust Aerosols Constrained By Measured Dust Shape Distributions

Most global aerosol models approximate dust as spherical particles, whereas most remote sensing retrieval algorithms approximate dust as spheroidal particles with a shape distribution that conflicts with measurements. These inconsistent and inaccurate shape assumptions generate biases in dust single-scattering properties. Here, we obtain dust single-scattering properties by approximating dust as triaxial ellipsoidal particles with observationally constrained shape distributions. We find that, relative to the ellipsoidal dust optics obtained here, the spherical dust optics used in most aerosol models underestimate dust single-scattering albedo, mass extinction efficiency, and asymmetry parameter for almost all dust sizes in both the shortwave and longwave spectra. We further find that the ellipsoidal dust optics are in substantially better agreement with observations of the scattering matrix and linear depolarization ratio than the spheroidal dust optics used in most retrieval algorithms. However, relative to observations, the ellipsoidal dust optics overestimate the lidar ratio by underestimating the backscattering intensity by a factor of ∼2. This occurs largely because the computational method used to simulate ellipsoidal dust optics (i.e., the improved geometric optics method) underestimates the backscattering intensity by a factor of ∼2 relative to other computational methods (e.g., the physical geometric optics method). We conclude that the ellipsoidal dust optics with observationally constrained shape distributions can help improve global aerosol models and possibly remote sensing retrieval algorithms that do not use the backscattering signal.

Dust↗

NASA NTRSDate not supplied

Advancing Satellite-Constrained Modeled Air-Sea CO 2 Fluxes With a Focus on the Strength of the Southern Ocean Carbon Sink

Challenge and Motivation: The ocean plays a critical role in mitigating climate change by removing approximately a quarter of annual anthropogenic CO 2 emissions from the atmosphere. Model-based estimates point to the Southern Ocean as a key marine region, responsible for approximately 40 % of the anthropogenic carbon uptake by the global ocean. However, the contemporary strength of the Southern Ocean carbon sink has recently come into question. On the one hand, airborne-based observations of atmospheric CO 2 gradients indicate that the Southern Ocean represents a strong net sink of atmospheric CO 2 , consistent in magnitude with atmospheric inversion estimates and surface-ocean partial pressure of CO 2 (pCO 2 )-based products. On the other hand, estimates of pCO 2 based on in situ pH measurements taken by biogeochemical profiling floats yield strong wintertime outgassing fluxes that greatly reduce the Southern Ocean’s annually integrated CO 2 uptake. This uncertainty in the strength of the Southern Ocean air-sea CO 2 flux and its role in the global carbon cycle hinders our ability to constrain global carbon fluxes, one of the major goals of NASA’s Carbon Monitoring System (CMS). Opportunity: The NASA Ocean Biogeochemical Model (NOBM) produces near-global pCO 2 and air-sea CO 2 flux estimates that are currently included into the NASA’s Goddard Earth Observing System (GEOS) models in support of the CMS effort to monitor global carbon fluxes. The NOBM assimilates ocean color data to improve the representation of biogeochemical fluxes and overcome spatial and temporal gaps in the space-based retrievals. Here, we propose to advance the satellite-constrained flux estimates by investigating the uncertainties in the Southern Ocean air-sea CO 2 flux produced by the NOBM, and assess the value that remote sensing ocean color data can have in providing improved estimates of carbon fluxes in the ocean. Our proposed work includes the delivery of refined in situ float-based carbon fluxes to serve as a constraint on the model-based estimates. Taking advantage of the model’s integration of satellite ocean color data to represent multiple phytoplankton groups, we propose to deliver maps of biogenic carbon export specific to each modeled phytoplankton type and investigate the role of ecological plankton complexity in regulating marine carbon uptake and export. Goals: (a) Delivery of seasonally-adjusted float-based Southern Ocean air-sea CO 2 fluxes: We will produce updated and improved float-based air-sea CO 2 fluxes that will serve as a bias-reduced float-based constraint to evaluate our model-based estimates of the NOBM. (b) Investigation of uncertainties in Southern Ocean air-sea CO 2 flux from the NOBM: Modeled air-sea carbon fluxes will be evaluated against the updated float product as well as ship- and airborne-based data to identify uncertainties and potential model deficiencies. (c) Delivery of model-based carbon export partitioning by phytoplankton functional types (PFTs): We will produce depth-resolved maps of particulate organic export production integrated for all phytoplankton groups and allocated to each individual PFT in the model. The expected significance of this goal is to quantify the role that the functional-oriented diversity in phytoplankton groups represented in the NOBM plays in regulating air-sea CO 2 fluxes in the Southern Ocean.

Lionel A. Arteaga↗

NASA NTRS2024

Stellar Occultation Observations to Constrain the Stratosphere of Uranus for Aerocapture

Background on Uranus: Voyager 2 (V2) UV stellar and solar occultations at Uranus detected a warm stratosphere and extremely hot thermosphere [1, 2], far in excess of solar irradiance [3, 4] and internal heating [5, 6]. New theories to explain similar heating at Jupiter [7] and Saturn [8] cannot be tested at Uranus due to a dearth of reliable measurements. In [9, 10], we reprocessed 26 archival Earth-based stellar occultations by Uranus (1977-1996), finding stratospheric temperatures (~200 K) warmer than the original (~100 K), but in stark tension with V2 (~300-500 K). In [10], we built a physics-based, 1-D atmospheric model (see Fig 1) that finds a nearly isothermal stratosphere and a dynamic heat sink in the lower thermosphere. Aerocapture: Aerocapture is spacecraft maneuver that uses a single deep dip to enter orbit. It could decrease cruise time and launch mass for a Uranus mission, but the greatest impediment is uncertain stratospheric densities of Uranus [11]. Aims: 1) Observe and process many high S/N Uranus stellar occultations in the next decade; 2) constrain stratospheric densities for aerocapture; 3) better understand the energy balance; 4) determine stratospheric changes since 1996. Upcoming Occultations: We will present our observing plan for the 2025 April Uranus occultation (K mag 8) and discuss the best-in-a-century 2031 event (K mag 4). We will discuss other events in the early 2030s [12] [13], predicted constraints on density, and simulations of aerocapture for UOP. We will discuss the Shadow Chaser, a small satellite concept for observing occultations from Earth orbit [12]. Conclusions: New stellar occultations can vastly improve profiles of the stratosphere of Uranus; this is critical for understanding energy circulation and constraining densities for using aerocapture on UOP. References: [1] Herbert, F. et al. (1987). JGR. [2] Stevens, M. et al. (1993). Icarus. [3] Marley, M. & McKay, C. (1999). Icarus, [4] Li, C. et al. (2018). JQRST. [5] Pearl, J. et al. (1990). Icarus. [6] Melin, H (2020). Nat Astron. [7] O’Donoghue, J. et al. (2021) Nature. [8] Mueller-Wodarg, I. et al. (2019) GRL. [9] Saunders, W. et al. (2023). PSJ. [10] Saunders, W. et al. (2024). PSJ. [11] Report of the Aerocapture Demonstration Relevance Assessment Team (2023). [12] Saunders, W. et al. (2022). P&SS. [13] French, R. & Souami, D. (2023) PSJ.

William Saunders↗

NASA NTRSDate not supplied

Content and Representation of Information Needed to Support Time-Constrained Problem Solving

NASA’s current mission-operations paradigm originated with Project Mercury and endured with minimum evolution through the Apollo Program, Space Shuttle Program, and ISS missions. At its foundation is a near-complete real-time dependence on a ground team to manage the combined state of the mission, vehicle, and crew. Utilizing many engineers and operators with broad and deep expertise; large, distributed datasets including extensive telemetry; and expansive analytical and computing power, this ground team has served as the safety net for crewed spaceflight missions over the past 60 years. This approach must change to address challenges associated with missions beyond low Earth orbit (BLEO), including infrequent resupply, reduced ability to evacuate, and delayed communications that prohibit real-time operational support. We anticipate that a necessary part of this change will be increased independence for the crew, as roles and responsibilities traditionally performed by ground teams move on board the vehicle. While many risks are associated with Earth-independent operations, one particular concern is ensuring that the crew will have adequate onboard support to perform urgent problem solving when communication with the ground is delayed or intermittent. A key resource that enables the ground team to respond to anomalies quickly and effectively is the extraordinary expertise and experience it possesses. It is comprised of 80+ experts on at any given time, with a combined 600+ years of system-specific experience across 22 unique console disciplines. A small crew will face the unprecedented challenge of independently responding to anomalies that have historically been handled by a team 20 times their size. Another important resource upon which the ground heavily relies to support procedure execution and anomaly response is data. The amount of telemetry data that each flight controller monitors is extensive. In addition, as the ground team works to further assess impacts, trouble shoot, identify workarounds, and oversee procedure execution, it accesses and synthesizes engineering and procedure information, as well as system build, test, and configuration documentation. It is not feasible nor useful to put all these data onboard as crews become more Earth independent. Each member of a small Mars mission small crew will have multiple roles beyond monitoring telemetry and data gathering, and multiple roles within anomaly resolution processes, thereby limiting their capacity for copious amounts of information. Moreover, while access is necessary, it alone is insufficient. Information will need to be compiled, refined, and represented appropriately to support the crew’s reduced attention and expertise. This work seeks to understand the content and representation of information needed to support time-constrained problem solving and decision making by the crew without real-time ground support. To build this understanding, we first surveyed the literature, focusing on how expert problem solvers construct and manipulate their mental models. Next, we interviewed expert problem solvers in spaceflight and analogous domains and surveyed industry solutions for data presentation. Finally, we analyzed current spaceflight operations by investigating flight controller anomaly resolution processes during ISS training simulations and real operational events. These methods led to creating a problem-solving framework that details common themes and features of attending to, assessing, analyzing, and acting on problems in complex, time-constrained domains. Using this framework and the results of our analysis, we identified conceptual data representations needed for crew-led problem-solving. Preliminary onboard user interface concepts to meet identified needs will be presented.

anomaly response↗

NASA NTRSDate not supplied

Variable Lidar Ratios for Marine and Dusty Marine Using MODIS AOD Constrained Retrievals and GOCART Model Simulations and their Impact on Level 2 CALIPSO Data Products in Version 5

The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) onboard CALIPSO provided global measurements of attenuated backscatter profiles of various tropospheric aerosol species from June 2006 through June 2023. Extinction profiles are retrieved from these backscatter measurements by assuming a value for the extinction-to-backscatter or lidar ratio (LR). Up until version V4.51 of the data products, only a constant global value for each of the species has been used, spatially and temporally. However, it has been well known from various ground-based measurements that LRs of each aerosol species can potentially vary spatially as well seasonally. For the forthcoming Version 5 of the CALIPSO products, the CALIPSO team will implement variable lidar ratios at 532 nm for the species classified as “marine” and “dusty marine”. Here we present the essential elements of this scheme, which involves estimating lidar ratios by constraining Fernald solutions for the CALIOP particulate backscatter profiles using aerosol optical depths (AOD) from collocated MODIS retrievals. To account for the lack of measurements in various regions and seasons (e.g., Arctic winters), we leverage collocated model sea-salt volume fractions (SSVF) simulated by the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model and use an empirical relationship between the SSVF and LR to build hybrid climatological maps for the entire globe, i.e., using the modelled values when reliable values of the constrained LRs are not available. Initial evaluation of the resulting extinction profiles and corresponding AODs, both globally and in specific regions are presented using a limited amount of data. The primary improvement in AOD occurs in the coastal areas, like the Arabian Sea and Bay of Bengal. The estimated marine LR values in these regions are significantly higher than the constant value of 23 sr used in previous data releases, likely due to mixing with offshore pollution which results in higher AODs. Initial validation results using the CALIPSO Ocean Derived Column Optical Depth (ODCOD) retrievals and ground-based AERONET AOD measurements are presented.

CALIPSO↗

NASA NTRS2026

LAI Assimilation Schedules to Constrain Uncertain Cultivars and Soils in CERES-Maize

In anticipation of large-domain crop model applications where precise local configuration and calibration is not possible, we describe benefits and potential drawbacks of employing a crop pest module to achieve leaf area index (LAI) assimilation into a high performing CERES-Maize crop model configuration at a field experiment site in Perry, Iowa. Simulation experiments explore the use of MODIS satellite-derived LAI to constrain and adjust LAI to counter imprecise cultivar and soil configurations often occurring in the absence of high-quality local information. Simulations using single-day, window, and continuous LAI replacement across 5 cultivars and 2 soil calibration approaches for nine corn rotation years from 2004 to 2020 led to different yield outcomes and reverberations throughout the field environment. Evaluating variance and mean bias, results indicate minimal interventions in early vegetative and grain-filling stages were more beneficial than use of continuous LAI adjustments, as they minimized disruptions to the internal resource balances governing plant stresses and grain production. LAI adjustment was particularly helpful in constraining growth related to uncertain thermal unit requirements and leaf tip appearance rates (P1 and PHINT cultivar parameters, respectively). Findings underscore the need to assimilate additional state variables to ensure internal biophysical coherence. This approach shows promise for applications spanning wider domains with prediction time pressure where detailed configuration, more complex assimilation methods, or recalibration of crop model parameters may not be practical.

Phenology↗

DOE OSTI2020

Constraining the Charge-Sign and Rigidity-Dependence of Solar Modulation

Our ability to identify the sources of cosmic rays and understand how these particles propagate through the interstellar medium is hindered by the combined effects of the solar wind and its embedded magnetic field, collectively known as solar modulation. In this paper, we build upon our previous work to model and constrain the effects of solar modulation on the cosmic-ray spectrum, using data from AMS-02 and BESS Polar II collected between 2007 and 2012, during which the heliospheric magnetic field was in a state of negative polarity. Our model uses measurements of the heliospheric magnetic field and the tilt angle of the heliospheric current sheet to accurately predict the effects of solar modulation as a function of time, charge, and rigidity. By incorporating data from a period of negative polarity, we have been able to robustly observe and constrain the charge-dependent effects of solar modulation.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

Physics-constrained Deep Recurrent Neural Models of Building Thermal Dynamics

We develop physics-constrained and control-oriented predictive deep learning models for the thermal dynamics of a real-world commercial office building. The proposed method is based on the systematic encoding of physics-based prior knowledge into a structured recurrent neural architecture. Specifically, our model mimics the structure of the building thermal dynamics model and leverages penalty methods to model inequality constraints. Additionally, we use constrained matrix parameterization based on the Perron-Frobenius theorem to bound the eigenvalues of the learned network weights. We interpret the stable eigenvalues as dissipativeness of the learned building thermal model. We demonstrate the effectiveness of the proposed approach on a dataset obtained from an office building with $20$ thermal zones.

Building Energy, structured neural networks↗

DOE OSTI2023

Interpreting Primal-Dual Algorithms for Constrained Multiagent Reinforcement Learning: Preprint

We study multiagent reinforcement learning (MARL) with constraints. This setting is gaining importance as MARL algorithms find new applications in real-world systems ranging from power grids to drone swarms. Most constrained MARL (C-MARL) algorithms use a primal-dual approach to enforce constraints through a penalty function added to the reward. In this paper, we study the structural effects of the primal-dual approach on the constraints and value function. First, we show that using the constraint evaluation as the penalty leads to a weak notion of safety, but by making simple modifications to the penalty function, we can enforce meaningful probabilistic safety constraints. Second, we show that the penalty term changes the value function in a way that is easy to model, and demonstrate the consequences of not doing so. We conclude with simulations in a simple constrained multiagent environment to back up the theoretical results.

data-driven control↗

DOE OSTI2025

Compressing Vision Transformers in Geospatial Transfer Learning with Manifold-Constrained Optimization

Deploying geospatial foundation models on resource-constrained edge devices demands compact architectures that maintain high downstream performance. However, their large parameter counts and the accuracy loss often induced by compression limit practical adoption.In this work, we leverage manifold-constrained optimization framework DLRT to compress large vision transformer–based geospatial foundation models during transfer learning. By enforcing structured low-dimensional parameterizations aligned with downstream objectives, this approach achieves strong compression while preserving task-specific accuracy. We show that the method outperforms of-the-shelf low-rank methods as LoRA. Experiments on diverse geospatial benchmarks confirm substantial parameter reduction with minimal accuracy loss, enabling high-performing, on-device geospatial models.

Snyder, Thomas [Yale University]↗

DOE OSTI2020

Moment preserving constrained resampling with applications to particle-in-cell methods

The Moment Preserving Constrained Resampling (MPCR) algorithm for particle resampling is introduced and applied to particle-in-cell (PIC) methods to increase simulation accuracy, reduce compute cost, and/or avoid numerical instabilities. The general algorithm partitions the system space into smaller subsets and resamples the distribution within each subset. Further, the algorithm is designed to conserve any number of particle and grid moments with a high degree of accuracy (i.e. machine accuracy). The effectiveness of MPCR is demonstrated with several numerical tests, including a use-case study in gyrokinetic fusion plasma simulations. Finally, the computational cost of MPCR is negligible compared to the cost of particle evolution in PIC methods, and the tests demonstrate that periodic particle resampling yields a significant improvement in the accuracy and stability of the results.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

DOE OSTI2020

PyCDFT: A Python package for constrained density functional theory

In this paper, we present PyCDFT, a Python package to compute diabatic states using constrained density functional theory (CDFT). PyCDFT provides an object-oriented, customizable implementation of CDFT, and allows for both single-point self-consistent-field calculations and geometry optimizations. PyCDFT is designed to interface with existing density functional theory (DFT) codes to perform CDFT calculations where constraint potentials are added to the Kohn–Sham Hamiltonian. Here, we demonstrate the use of PyCDFT by performing calculations with a massively parallel first-principles molecular dynamics code, Qbox, and we benchmark its accuracy by computing the electronic coupling between diabatic states for a set of organic molecules. We show that PyCDFT yields results in agreement with existing implementations and is a robust and flexible package for performing CDFT calculations. The program is available at https://dx.doi.org/10.5281/zenodo.3821097.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗