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All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Large-Scale Parallel Unstructured Mesh Computations for 3D High-Lift Analysis

A complete "geometry to drag-polar" analysis capability for three-dimensional high-lift configurations is described. The approach is based on the use of unstructured meshes in order to enable rapid turnaround for complicated geometries which arise in high-lift con gurations. Special attention is devoted to creating a capability for enabling analyses on highly resolved grids. Unstructured meshes of several million vertices are initially generated on a work-station, and subsequently refined on a supercomputer. The flow is solved on these refined meshes on large parallel computers using an unstructured agglomeration multigrid algorithm. Good prediction of lift and drag throughout the range of incidences is demonstrated on a transport take-off configuration using up to 24.7 million grid points. The feasibility of using this approach in a production environment on existing parallel machines is demonstrated, as well as the scalability of the solver on machines using up to 1450 processors.

Mavriplis, D. J.↗
NASA NTRS2007

Multi-Grid-Cell Validation of Satellite Aerosol Property Retrievals in INTEX/ITCT/ICARTT 2004

Aerosol transport off the US Northeast coast during the Summer 2004 International Consortium for Atmospheric Research on Transport and Transformation (ICARTT) Intercontinental Chemical Transport Experiment (INTEX) and Intercontinental Transport and Chemical Transformation (ITCT) experiments produced a wide range of aerosol types and aerosol optical depth (AOD) values, often with strong horizontal AOD gradients. In these conditions we flew the 14-channel NASA Ames Airborne Tracking Sun photometer (AATS) on a Jetstream 31 (J31) aircraft. Legs flown at low altitude (usually less than 100 m ASL) provided comparisons of AATS AOD spectra to retrievals for 90 grid cells of the satellite radiometers MODIS-Terra, MODIS-Aqua, and MISR, all over the ocean. Characterization of the retrieval environment was aided by using vertical profiles by the J31 (showing aerosol vertical structure) and, on occasion, shipboard measurements of light scattering and absorption. AATS provides AOD at 13 wavelengths lambda from 354 to 2138 nm, spanning the range of aerosol retrieval wavelengths for MODIS over ocean (466-2119 nm) and MISR (446-866 nm). Midvisible AOD on low-altitude J31 legs in satellite grid cells ranged from 0.05 to 0.9, with horizontal gradients often in the range 0.05 to 0.13 per 10 km. When possible, we used ship measurements of humidified aerosol scattering and absorption to estimate AOD below the J31. In these cases, which had J31 altitudes 60-110 m ASL (typical of J31 low-altitude transects), estimated midvisible AOD below the J31 ranged from 0.003 to 0.013, with mean 0.009 and standard deviation 0.003. These values averaged 6 percent of AOD above the 53 1. MISR-AATS comparisons on 29 July 2004 in 8 grid cells (each -17.6 km x 17.6 km) show that MISR versions 15 and 16 captured the AATS-measured AOD gradient (correlation coefficient R2 = 0.87 to 0.92), but the MISR gradient was somewhat weaker than the AATS gradient. The large AOD (midvisible values up to -0.9) and differing gradients in this case produced root-mean-square (RMS) MISR-AATS AOD differences of 0.03 to 0.21 (9 to 31%). MISR V15 Angstrom exponent alpha (= -dlnAOD/dln lambda) was closer to AATS than was MISR V16. MODIS-AATS AOD comparisons on 8 overpasses using 61 grid cells (each nominally 10 km x 10 km) had R2 approximately 0.97, with RMS AOD difference approximately 0.03 (approximately 20%). About 87% of the MODIS AOD retrievals differed from AATS values by less than the predicted MODIS over-ocean uncertainty, Delta tau = plus/minus 0.03 plus/minus 0.05 tau. In contrast to the small MODIS-AATS differences in AOD, MODIS-AATS differences in Angstrom exponent alpha were large: RMS differences for alpha (553, 855 nm) were 0.28 for MODIS-Terra and 0.64 for MODIS-Aqua; RMS differences for alpha (855, 2119 nm) were larger still, 0.61 for MODIS-Terra and 1.14 for MODIS-Aqua. The largest MODIS-AATS Angstrom exponent differences were associated with small AOD values, for which MODIS AOD relative uncertainty is large. Excluding cases with AOD(855 nm) less than 0.1 reduced MODIS-AATS alpha differences substantially. In one grid cell on 21 July 2004, smoke over cloud appeared to impair the MODIS-Aqua cloud mask, resulting in retrieved AODs that significantly exceeded AATS values. Experiments with extending MODIS retrievals into the glint mask yielded MODIS AODs consistently less than AATS AODs, especially at long wavelength, indicating that the current MODIS glint mask limits should not be reduced to the extent tried here. The sign of the AOD differences within the glint mask (MODIS AOD less than AATS AOD) is consistent with ship-measured wind speeds there.

Russell, P. B.↗
DOE OSTI2020

Reliability of emergency and standby diesel generators: Impact on energy resiliency solutions

Emergency diesel generators are the most common form of backup power for critical loads when the grid fails and are most often deployed as stand-alone generators (<2000 kW) tied to individual buildings for hospitals, emergency services, military bases, ports, airports, industries, and commercial facilities. Understanding the finite reliability of emergency diesel generators during continuous operation is critical for energy planners, managers, and end-users. A new analysis of two large non-public emergency diesel generator operational data sets shows that commonly used reliability metrics are inadequate to predict the performance during a grid outage. Additional metrics addressing the likelihood of an emergency diesel generator to be available at the time an outage starts, successfully start and carry load, and constantly run for the duration of the outage are needed to predict the continuous run-time reliability of emergency diesel generators during a grid outage. This is the first analysis of the reliability of modern generators that follow standard maintenance protocols commonly used for backup power and these new metrics are shown to be dependent on the level of emergency diesel generator maintenance with values that can vary by more than an order of magnitude. Even using the new metrics for well-maintained emergency diesel generators, the analysis shows that the single emergency diesel generators configurations are only 80% likely to provide power for the duration of a two-week grid outage.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2024

Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Achieving success with grid-interactive efficient buildings (GEBs) is closely tied to the utilization of flexible loads. A valuable strategy involves the implementation of precooling techniques before high-demand events, such as peak hours, by adjusting zone air temperature setpoints. This leads to a reduction in thermal loads and peak electricity demand during these times, as the building’s thermal mass stores and subsequently releases thermal energy. However, the effectiveness of the pre-cooling optimization is highly contingent on specific conditions such as building thermal properties, weather conditions, utility rate structure, HVAC equipment sizing, etc. Therefore, investigating the impacts of these condition-specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Here, the optimal thermostat schedule was parameterized using three optimization variables: the precooling start time, the precooling end time, and the precooling temperature setpoint. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. In addition, we investigated the impact of different influencing factors on the optimal precooling strategy. These factors include building thermal mass, outdoor air conditions, and energy price profiles. Using high-performance computing, we simulated a total of 225 scenarios, consisting of three levels of thermal mass, five typical outdoor air temperature profiles, and fifteen time-of-use price plans. The results demonstrate that optimal thermostat scheduling could save substantial energy cost in medium-sized office buildings with heavy thermal mass but with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. The study also highlights the need to account for zone diversity and recognize that a one-size-fits-all-zone setpoint schedule may not be suitable for all zones and can lead to unnecessary energy wastage. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. Although cost savings are comparable under certain conditions with the same cooling load, observed deviations in energy penalty indicate potential disparities in the efficiency of the HVAC system during the load-shifting process. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Model Predictive Voltage Control of Large-Scale PV or Hybrid PV-BESS Plants

Increased penetration level of inverter-based resources (IBRs) and renewable energy in the power grid has called for more requirements from the control of IBRs. In this paper, the voltage-reactive power control of a photovoltaic (PV) power plant or hybrid PV-battery energy storage system (BESS) plant connected to a bulk power grid, whilst meeting the grid requirements, is studied. In this paper, a continuous-set model predictive control (MPC) formulation is proposed for voltage-reactive power control. For the same, an aggregated dynamic PV plant model is developed based on the recursive system equivalencing method. The formulation is then implemented in PSCAD simulation on a 125 MW PV plant or hybrid PV-BESS plant. The MPC implementation achieves 10.13% voltage improvement based on PSCAD simulation results in a balanced fault case study. Simulation results further demonstrate that MPC provides improved voltage support over the conventional proportional-integral (PI) controller post-fault occurrence.

Abu rub, Omar↗
DOE OSTI2023

A novel large-scale EV charging scheduling algorithm considering V2G and reactive power management based on ADMM

Electric vehicle aggregators (EVAs) that utilize vehicle-to-grid (V2G) technologies can function as both controllable loads and virtual power plants, providing key energy management services to the distribution system operator (DSO). EVAs can also balance the grid’s reactive power as a virtual static VAR compensator (SVC) and provide voltage stability by utilizing advanced electric vehicle (EV) chargers that are capable of four-quadrant operations to provide reactive power management. Finally, managed charging can benefit EVAs themselves by minimizing power factor penalties in their electricity bills. In this paper, we propose a novel EV charging scheduling algorithm based on a hierarchical distributed optimization framework that minimizes peak load and provides reactive power compensation for the DSO by collaboration with EVAs that manage both the active and the reactive charging and discharging power of participating EVs. Utilizing the alternative direction method of multipliers (ADMM), the proposed distributed optimization approach scales well with increased EV charging infrastructure by balancing active and reactive power while decreasing computational burden. In our proposed hierarchical approach, each EVA schedules the active and reactive EV charging and discharging power for 1) reactive power compensation in order to minimize power factor penalty and electricity cost accrued by the EVA, 2) satisfaction of each EV’s energy demand at minimal charging cost, and 3) peak shaving and load management for the DSO. When compared with an uncoordinated charging model, the efficacy of this proposed model is successfully demonstrated through a 300% decreased peak EV load for the DSO, 28% lower electricity costs for EV users, and 98.55% smaller power factor penalty, along with 17.58% lower overall electricity costs, for EVAs. The performance of our approach is validated in a case study with 50 EVs at multiple EVAs in an IEEE 13-bus test case and compared the results with uncoordinated EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2019

Intercomparison of Aerosol Volume Size Distributions Derived from AERONET Ground-Based Remote Sensing and LARGE in Situ Aircraft Profiles During the 2011–2014 DRAGON and DISCOVER-AQ Experiments

Aerosol volume size distribution (VSD) retrievals from the Aerosol Robotic Network (AERONET) aerosol monitoring network were obtained during multiple DRAGON (Distributed Regional Aerosol Gridded Observational Network) campaigns conducted in Maryland, California, Texas and Colorado from 2011 to 2014. These VSD retrievals from the field campaigns were used to make comparisons with near-simultaneous in situ samples from aircraft profiles carried out by the NASA Langley Aerosol Group Experiment (LARGE) team as part of four campaigns comprising the DISCOVER-AQ (Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality) experiments. For coincident (1 h) measurements there were a total of 91 profile-averaged fine-mode size distributions acquired with the LARGE ultra-high sensitivity aerosol spectrometer (UHSAS) instrument matched to 153 AERONET size distributions retrieved from almucantars at 22 different ground sites. These volume size distributions were characterized by two fine-mode parameters, the radius of peak concentration (rpeak_conc) and the VSD fine-mode width (widthpeak_conc). The AERONET retrievals of these VSD fine-mode parameters, derived from ground-based almucantar sun photometer data, represent ambient humidity values while the LARGE aircraft spiral profile retrievals provide dried aerosol (relative humidity; RH< 20 %) values. For the combined multiple campaign dataset, the average difference in rpeak_conc was 0:0330:035 μm (ambient AERONET values were 15.8% larger than dried LARGE values), and the average difference in widthpeak_conc was 0:0420:039 μm (AERONET values were 25.7% larger). For a subset of aircraft data, the LARGE data were adjusted to account for ambient humidification. For these cases, the AERONET–LARGE average differences were smaller, with rpeak_conc differing by 0:0110:019 μm (AERONET values were 5.2% larger) and widthpeak_conc average differences equal to 0:0300:037 μm (AERONET values were 15.8% larger).

Schafer, Joel S.↗
DOE OSTI2023

Frequency Recovery in Power Grids Using High-Performance Computing

Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

nonlinear model predictive control↗
DOE OSTI2023

A Gradient Based Subgrid-Scale Parameterization for Ocean Mesoscale Eddies

Mesoscale eddies play an important role in transport of heat and biogeochemical tracers in the global ocean circulation. Resolving these energetic eddies, however, is challenging in ocean general circulation models (OGCM) because it requires a horizontal grid spacing of ≲1/8° that is computationally expensive. As a result, we are required to parameterize mesoscale eddy effects on large-scale ocean flows. In this work, we introduce a new subgrid-scale (SGS) model that is developed based on a Taylor series expansion of resolved variables to parameterize subgrid mesoscale eddy transports and momentum fluxes in OGCM. We have performed an a priori study to evaluate the performance of our new gradient model using high-resolution ocean simulations. Our results show that the gradient model well predicts the actual SGS thickness fluxes in the zonal and meridional directions in coarse-resolution simulations with the grid spacing ≳1/4°. The unresolved kinetic energy at the ocean surface is also skillfully estimated. More importantly, unlike current mesoscale eddy parameterizations, which are mainly developed based on an assumption of flat bottom ocean, our new SGS model can capture the structure of unresolved standing meanders at the ocean surface. We have also developed a dynamic procedure for setting in non-dimensional parameters in our new parameterization through a non-ad hoc and tuning-free method. Overall, this work suggests that implementing the gradient model in OGCM can improve the model accuracy with an affordable computational cost in eddy-permitting and non-eddying simulations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A sharp interface Lagrangian-Eulerian method for flexible-body fluid-structure interaction

This paper introduces a sharp-interface approach to simulating fluid-structure interaction (FSI) involving flexible bodies described by general nonlinear material models and across a broad range of mass density ratios. This new flexible-body immersed Lagrangian-Eulerian (ILE) scheme extends our prior work on integrating partitioned and immersed approaches to rigid-body FSI. Our numerical approach incorporates the geometrical and domain solution flexibility of the immersed boundary (IB) method with an accuracy comparable to body-fitted approaches that sharply resolve flows and stresses up to the fluid-structure interface. Unlike many IB methods, our ILE formulation uses distinct momentum equations for the fluid and solid subregions with a Dirichlet-Neumann coupling strategy that connects fluid and solid subproblems through simple interface conditions. As in earlier work, we use approximate Lagrange multiplier forces to treat the kinematic interface conditions along the fluid-structure interface. This penalty approach simplifies the linear solvers needed by our formulation by introducing two representations of the fluid-structure interface, one that moves with the fluid and another that moves with the structure, that are connected by stiff springs. This approach also enables the use of multi-rate time stepping, which allows us to use different time step sizes for the fluid and structure subproblems. Our fluid solver relies on an immersed interface method (IIM) for discrete surfaces to impose stress jump conditions along complex interfaces while enabling the use of fast structured-grid solvers for the incompressible Navier-Stokes equations. The dynamics of the volumetric structural mesh are determined using a standard finite element approach to large-deformation nonlinear elasticity via a nearly incompressible solid mechanics formulation. This formulation also readily accommodates compressible structures with a constant total volume, and it can handle fully compressible solid structures for cases in which at least part of the solid boundary does not contact the incompressible fluid. Selected grid convergence studies demonstrate second-order convergence in volume conservation and in the pointwise discrepancies between corresponding positions of the two interface representations as well as between first and second-order convergence in the structural displacements. The time stepping scheme is also demonstrated to yield second-order convergence. To assess and validate the robustness and accuracy of the new algorithm, comparisons are made with computational and experimental FSI benchmarks. Test cases include both smooth and sharp geometries in various flow conditions. Furthermore, we also demonstrate the capabilities of this methodology by applying it to model the transport and capture of a geometrically realistic, deformable blood clot in an inferior vena cava filter.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Eulerian thermo-mechanical simulations of heterogeneous solid propellants using an approximate projection method

We present a mathematical model that describes thermo-mechanical deformations and thermal gradients on the unsteady burning of a heterogeneous solid propellant. A scaling study shows that the deformations in solid at combustion timescales can be treated as quasi-static. The resulting thermo-mechanical formulation is formulated on a Cartesian grid and makes use of a weak form of Chorin-type projection method to deal with large difference in shear modulus of constituent materials. Further, a one-dimensional verification study is carried out by comparing numerical simulations with those of an analytical model. In addition, convergence studies for a two-dimensional propellant sandwich configuration are presented for the stress, velocity, and reference map components. Finally, simulations are carried out for a two-dimensional random propellant pack and the time-averaged burn rate and strains are reported.

42 ENGINEERING↗
DOE OSTI2024

Multi-fidelity Fourier neural operator for fast modeling of large-scale geological carbon storage

Deep learning-based surrogate models have been widely applied in geological carbon storage (GCS) problems to accelerate the prediction of reservoir pressure and CO2 plume migration. Large amounts of data from physics-based numerical simulators are required to train a model to accurately predict the complex physical behaviors associated with this process. In practice, the available training data are always limited in large-scale 3D problems due to the high computational cost. Therefore, we propose to use a multi-fidelity Fourier neural operator (FNO) to solve large-scale GCS problems with more affordable multi-fidelity training datasets. FNO has a desirable grid-invariant property, which simplifies the transfer learning procedure between datasets with different discretization. Here, we first test the model efficacy on a GCS reservoir model being discretized into 110 k grid cells. The multi-fidelity model can predict with accuracy comparable to a high-fidelity model trained with the same amount of high-fidelity data with 81% less data generation costs. We further test the generalizability of the multi-fidelity model on a same reservoir model with a finer discretization of 1 million grid cells. This case was made more challenging by employing high-fidelity and low-fidelity datasets generated by different geostatistical models and reservoir simulators. We observe that the multi-fidelity FNO model can predict pressure fields with reasonable accuracy even when the high-fidelity data are extremely limited. The findings of this study can help for better understanding of the transferability of multi-fidelity deep learning surrogate models.

58 GEOSCIENCES↗
DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗
DOE OSTI2025

A nonhydrostatic formulation for MPAS-Ocean

The Model for Prediction Across Scales-Ocean (MPAS-Ocean) is an open-source, global ocean model and is one component of a family of climate models within the MPAS framework, including atmosphere, sea-ice, and land-ice models. Here, in this work, a new formulation for the ocean model is presented that solves the nonhydrostatic, incompressible Boussinesq equations on an unstructured, staggered, z-level grid. The introduction of this nonhydrostatic capability is necessary for the resolution of internal wave dynamics and large eddy simulations. Compared to the standard, hydrostatic formulation, a nonhydrostatic pressure solver and a vertical momentum equation are added, where the PETSc (Portable Extensible Toolkit for Scientific Computation) library is used for the inversion of a large sparse system for the nonhydrostatic pressure. Numerical results on a stratified seiche, internal solitary wave, overflow and lock-exchange test cases are presented, and the parallel efficiency of the code is evaluated using up to 1024 processors.

3D Poisson equation↗
DOE OSTI2020

Emergence of unprecedented climate change in projected future precipitation

The future time of emergence when precipitation changes due to anthropogenic influences begins to continuously exceed the previous maximum value is defined as the ‘tipping year’ Historical experiments and future experiments simulated by state-of-the-art climate models were utilized. A total of 510,000 time series from year 1856 to 2095 were generated by sampling the natural internal variability in precipitation. The time evolutions of internal variability in the whole time period were estimated from the combination of past and future experiments with preindustrial control experiments. A large ensemble size enabled an estimation of the probability density function of the tipping year at each grid point, providing precise information on the uncertainty of the projection. The tipping year of average precipitation emerges earlier in high latitudes than in lower latitudes. In some regions in lower latitudes and mid-latitudes, the tipping year of intense precipitation emerges faster than that of average precipitation. The tipping years of average and intense precipitation are earlier for higher anthropogenic forcing scenarios than for lower scenarios. The global average of the tipping year for intense precipitation might be attributed to the enhancement of the thermodynamic effect (moisture) rather than the dynamic effect (vertical motion).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

On decoupling the integrals of cosmological perturbation theory

ABSTRACT Perturbation theory (PT) is often used to model statistical observables capturing the translation and rotation-invariant information in cosmological density fields. PT produces higher order corrections by integration over linear statistics of the density fields weighted by kernels resulting from recursive solution of the fluid equations. These integrals quickly become high dimensional and naively require increasing computational resources the higher the order of the corrections. Here, we show how to decouple the integrands that often produce this issue, enabling PT corrections to be computed as a sum of products of independent 1D integrals. Our approach is related to a commonly used method for calculating multiloop Feynman integrals in quantum field theory, the Gegenbauer Polynomial x-Space Technique. We explicitly reduce the three terms entering the 2-loop power spectrum, formally requiring 9D integrations, to sums over successive 1D radial integrals. These 1D integrals can further be performed as convolutions, rendering the scaling of this method Nglog Ng with Ng the number of grid points used for each fast Fourier transform. This method should be highly enabling for upcoming large-scale structure redshift surveys where model predictions at an enormous number of cosmological parameter combinations will be required by Monte Carlo Markov Chain searches for the best-fitting values.

Slepian, Zachary↗
DOE OSTI2022

Handing off the outcome of binary neutron star mergers for accurate and long-term postmerger simulations

In this work, we perform binary neutron star (BNS) merger simulations in full dynamical general relativity with IllinoisGRMHD, on a Cartesian grid with adaptive-mesh refinement. After the remnant black hole has become nearly stationary, the evolution of the surrounding accretion disk on Cartesian grids over long timescales (~1s) is suboptimal, as Cartesian coordinates over-resolve the angular coordinates at large distances, and the accreting plasma flows obliquely across coordinate lines dissipating angular momentum artificially from the disk. To address this, we present the HandOff, a set of computational tools that enables the transfer of general relativistic magnetohydrodynamic (GRMHD) and spacetime data from IllinoisGRMHD to harm3d, a GRMHD code that specializes in modeling black hole accretion disks in static spacetimes over long timescales, making use of general coordinate systems with spherical topology. We demonstrate that the handoff allows for a smooth and reliable transition of GRMHD fields and spacetime data, enabling us to efficiently and reliably evolve BNS dynamics well beyond merger. We also discuss future plans, which involve incorporating advanced equations of state and neutrino physics into BNS simulations using the HandOff approach.

79 ASTRONOMY AND ASTROPHYSICS↗