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This talk presents the recent progress in building a predictive movement model for predicting conflict between soaring raptors and wind turbines. In particular, it details the recently developed numerical tool called Stochastic Soaring Raptor Simulator for simulating updraft-subsidized paths for soaring raptors through variety of wind conditions and the associated directional intent.
As next-generation imaging instruments and interferometers search for planets closer to their stars, they must contend with increasing orbital motion and longer integration times. These compounding effects make it difficult to detect faint planets but also present an opportunity. Increased orbital motion makes it possible to move the search for planets into the orbital domain, where direct images can be freely combined with the radial velocity and proper motion anomaly, even without a confirmed detection in any single epoch. In this paper, we present a fast and differentiable multimethod orbit-modeling and planet detection code called Octofitter. This code is designed to be highly modular and allows users to easily adjust priors, change parameterizations, and specify arbitrary function relations between the parameters of one or more planets. Octofitter further supplies tools for examining model outputs including prior and posterior predictive checks and simulation-based calibration. We demonstrate the capabilities of Octofitter on real and simulated data from different instruments and methods, including HD 91312, simulated JWST/NIRISS aperture masking interferometry observations, radial velocity curves, and grids of images from the Gemini Planet Imager. We show that Octofitter can reliably recover faint planets in long sequences of images with arbitrary orbital motion. This publicly available tool will enable the broad application of multiepoch and multimethod exoplanet detection, which could improve how future targeted ground- and space-based surveys are performed. Finally, its rapid convergence makes it a useful addition to the existing ecosystem of tools for modeling the orbits of directly imaged planets.
Geothermal deep direct use (DDU) has potential across a wide swath of the United States but is underutilized due to challenging project economics associated with developing a deep geothermal resource for a large-scale and variable heat demand. The National Renewable Energy Laboratory (NREL) and University of Oklahoma evaluated the feasibility of a geothermal district heating (GDH) and cooling system in two schools and 250 houses by utilizing existing oil and gas (O&G) wells in Tuttle, Oklahoma. Heating and cooling demand in the two schools and a typical single-family house were modeled using EnergyPlus building energy simulation software. The modeling results indicated that annual heating demand in two schools and 250 houses is approximately 2.61 GWhth, and cooling demand in the two schools is approximately 2.65 GWhth. In this scope, the techno-economic analysis (TEA) was conducted using the GEOPHIRES tool combined with the TOUGH2 reservoir simulator. The reservoir performance, including geothermal heat production capacity, was modeled by the reservoir simulator TOUGH2. Then, levelized cost of heat (LCOH) was calculated using GEOPHIRES version 3.0, which includes new features such as hourly heat load optimization and peak performance evaluation. Geothermal reservoir temperature was estimated as 90.5 degrees C at a total depth of 3.3 km by the regional average temperature gradient of 22.8 degrees C/km and validated by cation geothermometer calculations. Four production scenarios with two different well configurations and two different heat load profiles have been developed for well flow rates ranging between 3.1 kg/s and 9.3 kg/s. The LCOH of the district heating and cooling system was calculated between $95 and $210/MWh ($28/MMBtu to $62/MMBtu) for four different production scenarios. Typical natural gas prices for residential customers in Oklahoma have ranged from 9 to 19 $/MMBtu over the past decade, which indicates a challenge for deployment of such a GDH system.
Geothermal deep direct use (DDU) has potential across a wide swath of the United States but is underutilized due to challenging project economics associated with developing a deep geothermal resource for a large-scale and variable heat demand. The National Renewable Energy Laboratory (NREL) and University of Oklahoma evaluated the feasibility of a geothermal district heating (GDH) and cooling system in two schools and 250 houses by utilizing existing oil and gas (O&G) wells in Tuttle, Oklahoma. Heating and cooling demand in the two schools and a typical single-family house were modeled using EnergyPlus building energy simulation software. The modeling results indicated that annual heating demand in two schools and 250 houses is approximately 2.61 GWhth, and cooling demand in the two schools is approximately 2.65 GWhth. In this scope, the techno-economic analysis (TEA) was conducted using the GEOPHIRES tool combined with the TOUGH2 reservoir simulator. The reservoir performance, including geothermal heat production capacity, was modeled by the reservoir simulator TOUGH2. Then, levelized cost of heat (LCOH) was calculated using GEOPHIRES version 3.0, which includes new features such as hourly heat load optimization and peak performance evaluation. Geothermal reservoir temperature was estimated as 90.5 degrees C at a total depth of 3.3 km by the regional average temperature gradient of 22.8 degrees C/km and validated by cation geothermometer calculations. Four production scenarios with two different well configurations and two different heat load profiles have been developed for well flow rates ranging between 3.1 kg/s and 9.3 kg/s. The LCOH of the district heating and cooling system was calculated between $95 and $210/MWh ($28/MMBtu to $62/MMBtu) for four different production scenarios. Typical natural gas prices for residential customers in Oklahoma have ranged from 9 to 19 $/MMBtu over the past decade, which indicates a challenge for deployment of such a GDH system.
A rapid intelligent tutoring development system (RAPIDS) was developed to facilitate the production of interactive, real-time graphical device models for use in instructing the operation and maintenance of complex systems. The tools allowed subject matter experts to produce device models by creating instances of previously defined objects and positioning them in the emerging device model. These simulation authoring functions, as well as those associated with demonstrating procedures and functional effects on the completed model, required no previous programming experience or use of frame-based instructional languages. Three large simulations were developed in RAPIDS, each involving more than a dozen screen-sized sections. Seven small, single-view applications were developed to explore the range of applicability. Three workshops were conducted to train others in the use of the authoring tools. Participants learned to employ the authoring tools in three to four days and were able to produce small working device models on the fifth day.
The goal of this project was to create a simulation tool to assist in part design, reducing costs by eliminating the need for conservative material selection, and enabling alloy optimization to improve corrosion resistance. Thus, it helps decrease costs for existing engines and assists in the material and engine design for the engines of the future. To meet our stated goal, we developed the Stainless-Steel Alloy Corrosion (SStAC) tool, which: (1) Models corrosion of engine valves fabricated from 21-2N valve steel in an engine environment at temperatures up to 800 °C. (2) Runs in 1D for a fast estimate of the corrosion rate, and in 2D or 3D for more detailed simulations that represent any part geometry and predict the precise location and rate of corrosion and its impact on the mechanical and thermal behavior. (3) Was implemented using the open-source Multiphysics Object Oriented Simulation Environment (MOOSE). (4) Couples the corrosion model with mechanics and thermal transport models. The SStAC tool can predict the corrosion rate of 21-2N engine valves with less than 10% error.
Ocean-driven basal melting of Antarctic ice shelves plays an important role in the mass loss of the Antarctic Ice Sheet. Ice shelf cavity-resolving ocean models are a valuable tool for understanding ice shelf-ocean interactions and for simulating projections of ice shelf and ocean states under future climate. Designed to assess the current state of ice shelf–ocean modelling, the second Ice Shelf–Ocean Model Intercomparison Project, ISOMIP+, consists of 12 ocean model configurations submitted with a common, idealised experimental setup. Here, we focus on the experiments Ocean0–2 (Asay-Davis et al., 2016), which are ocean models with idealised, static ice shelf geometries, but where the ocean reaches a balance with prescribed far-field ocean conditions. Different thermal transfer coefficient values (ranging from 0.011 to 0.2) are used for each model in the melting parameterisation to achieve a common, tuned melt rate since the models cover a range of types of vertical coordinates, ice–ocean boundary layer treatments, and numerical schemes. These model differences lead to spread in the resultant ocean properties, circulation, boundary-layer structure and spatial distribution of melting. We also highlight similarities between models, such as a shared linear relationship across most models between melt rate and overturning and barotropic streamfunctions during the spin-up and spin-down, demonstrating a robust relationship between melt and circulation across models and forcing conditions. The ISOMIP+ results provide a systematic comparison of ice shelf cavity-capable ocean models. However, we also demonstrate the need for realistic ice shelf–ocean model intercomparison projects (some already underway) to assess model biases and inter-model variation against sparse observations. Further research is needed to understand the differences between models and further improve our modelled representations of the ice–ocean boundary layer and ice shelf cavity circulation.
The Computational Controls Workstation provides an integrated environment for the modeling, simulation, and analysis of Space Station dynamics and control. Using highly efficient computational algorithms combined with a fast parallel processing architecture, the workstation makes real-time simulation of flexible body models of the Space Station possible. A consistent, user-friendly interface and state-of-the-art post-processing options are combined with powerful analysis tools and model databases to provide users with a complete environment for Space Station dynamics and control analysis. The software tools available include a solid modeler, graphical data entry tool, O(n) algorithm-based multi-flexible body simulation, and 2D/3D post-processors. This paper describes the architecture of the workstation while a companion paper describes performance and user perspectives.
Thermal runaway (TR) modeling is one of the primary tools that can be used to overcome challenges associated with lithium-ion battery (LIB) safety. Among all LIB accidents that have occurred over the past decade, Internal Short Circuit (ISC) remains the most common trigger mechanism. Many available models in the literature either use a simplified approach to simulate ISC or completely ignore its contribution. The aim of this study is to understand the nature of the heat released for different types of ISC scenarios, including aluminum-anode, anode–cathode, and copper-cathode ISC. We study ISC behavior using a coupled electrochemical–thermal model with an integrated TR chemical kinetics solver built in the COMSOL Multiphysics framework. The time duration of heat release and the magnitude of the peak ISC current are studied as functions of parameters such as the size of the penetrating filament and the capacity of the cell. The numerical results are used to build an empirical model validated against the published experimental TR propagation data. Our model can be successfully used as a viable low-cost substitute in lower order (lumped) TR simulations to enable TR prevention and mitigation.
The project will continue the FY13 JSC IR&D (October-2012 to September-2013) effort in Travelling Wave Direct Energy Conversion (TWDEC) in order to demonstrate its potential as the core of a high potential, game-changing, in-space propulsion technology. The TWDEC concept converts particle beam energy into radio frequency (RF) alternating current electrical power, such as can be used to heat the propellant in a plasma thruster. In a more advanced concept (explored in the Phase 1 NIAC project), the TWDEC could also be utilized to condition the particle beam such that it may transfer directed kinetic energy to a target propellant plasma for the purpose of increasing thrust and optimizing the specific impulse. The overall scope of the FY13 first-year effort was to build on both the 2012 Phase 1 NIAC research and the analysis and test results produced by Japanese researchers over the past twenty years to assess the potential for spacecraft propulsion applications. The primary objective of the FY13 effort was to create particle-in-cell computer simulations of a TWDEC. Other objectives included construction of a breadboard TWDEC test article, preliminary test calibration of the simulations, and construction of first order power system models to feed into mission architecture analyses with COPERNICUS tools. Due to funding cuts resulting from the FY13 sequestration, only the computer simulations and assembly of the breadboard test article were completed. The simulations, however, are of unprecedented flexibility and precision and were presented at the 2013 AIAA Joint Propulsion Conference. Also, the assembled test article will provide an ion current density two orders of magnitude above that available in previous Japanese experiments, thus enabling the first direct measurements of power generation from a TWDEC for FY14. The proposed FY14 effort will use the test article for experimental validation of the computer simulations and thus complete to a greater fidelity the mission analysis products originally conceived for FY13.
The scope of this work addresses key issues associated with losses associated with the detonation wave and other processes internal to the RDE operation, as well as it develops modeling tools for the evaluation of these losses and exhaust emissions in RDEs. The main challenge in studying RDEs is that RDE performance is highly reliant on the specifics of the design so much so that simple/canonical systems alone cannot provide useful engineering information, but practical RDE designs are sufficiently complex and involve extreme operational environments that detailed access either experimentally (laser diagnostics, for instance) or computationally (direct numerical simulations) are as yet to become practical. To overcome this challenge, we have conducted a combined experimental/simulation/analytical study investigating key phenomena that control the characteristics of operation of RDEs. As a result, the study has developed tools and methods that can be used to evaluate performance and design approaches using reduced-physics models, with the assumptions validated using detailed simulations, and the model prediction tested using experimental observations. The specific objectives of the research were: (1) Develop and demonstrate a low-loss fully axial injection concept, taking advantage of stratification effects to alter the detonation structure and position the wave favorably within the combustor; (2) Obtain stability and operability characteristics of an RDE across operating conditions to aid in the development of operability and performance rules for the operations of other systems; and (3) Develop quantitative metrics for performance gain as well as quantitative description of the loss mechanisms through a combination of diagnostics development, reduced-order modeling, and detailed simulations. The work conducted here has made contribution on design of low-loss inlets that has broad application within the power generation industry for use with pressure gain combustion. The operability and stability of different designs, while focusing on axial air inlet designs, has been analyzed. The effect of nozzle and injection conditions was studied. Models and simulations of exhaust emissions, focusing on NOx emission has been developed and used to investigate how operation of the RDE affect NOx production using Lagrangian analysis of RDE simulations. This work has built on previous programs, with the goal of further understanding operation of RDEs and elevate the readiness of design consideration. In addition, a suite of diagnostic and modeling tools have been developed to obtain quantitative metrics on performance based on measurements, which can be readily transferred to other experimental configurations.
The Customer Avionics Interface Development and Analysis (CAIDA) team provides modeling and simulation software for the verification of the Launch Control System (LCS). In late 2015, CAIDA began development of the Data Exchange Message (DEM) Generator (DEMGen) and development of the DEM Modifier (DEMMod) in early 2017. DEMGen is able to mimic the telemetry streams normally sent by different simulators allowing increased user control and more telemetry instances. DEMMod takes in a telemetry stream and allows the modification of entire packets or simple measurement values. Together, these tools provide the capabilities to simulate and test complex launch scenarios to ensure LCS is fully prepared for any anomalous behavior during an actual launch. In early 2018, CAIDA began a new project called the CAIDA Advanced Telemetry Tool (CATT), which combined the code and documentation of DEMGen and DEMMod. CATT now allows the integration of new tools into a singular program providing compact and easy access. In the fall of 2018, the author worked with another intern, Antonio Negron, to develop several new CATT features along with proper documentation and unit testing. In the following spring, the author continued that work by integrating the features into CATT, solidifying the documentation, and expanding the testing to cover more cases. The outcome of both semesters includes an inspection engine for automated packet analysis, a packet-masking feature, and a multi-measurement sequencing feature.
Recent advancements in data science and high-performance computing are making it easier to run millions of building simulations, but meaningful visualization of such large datasets remains a challenge. This paper presents a new tool developed to view the results of large-scale OpenStudio simulations of national, regional, or local building stocks. The tool processes millions of simulations to calculate measure savings, utility bills, carbon emissions, primary energy, and cost-effectiveness metrics at a high geographic resolution. Interactive visualizations of the building characteristics, consumption, and measure savings data include proportional symbol maps and histogram plots and can be filtered by any building characteristic.
The goal of the project is to employ a combination of high-fidelity simulations and true-triaxial block fracturing tests at high temperature to explore the intricate relationship between in-situ stress and hydraulic fracture patterns and better characterize the in-situ stress at Utah FORGE. Laboratory experiments are used to validate numerical models and better understand the impact of various parameters (e.g., temperature, well orientation, stress, etc) on the hydraulic fracture nucleation process in EGS. The project will have a significant impact as it will (1) improve the characterization of the in-situ stress field at FORGE; (2) demonstrate how high-fidelity modeling tools can be employed to analyze data for EGS; (3) provide a unique set of high-temperature hydraulic fracturing experimental results for EGS to help identifying the most important components for in-situ stress estimation and to validate the current in-situ stress estimation theory and establish a strong foundation for proposing a new one; (4) provide a validated set of numerical tools in an open source simulation framework (GEOS) that can be used to model EGS.
The Solar Dynamics Observatory (SDO) mission, part of the Living With a Star program, is a geosynchronous satellite with tight pointing requirements. Due to a large amount of liquid propellant, a detailed slosh analysis is required to ensure the tight pointing budget can be satisfied. Much of the high fidelity slosh analysis and simulation has been performed via computational fluid dynamics. Even though this method of simulation is very accurate, it requires significant computational effort and specialized knowledge, limiting the ability of the SDO project to access fluid dynamics simulations at will. Furthermore, it is very difficult to incorporate most of these models into simulations of the overall spacecraft and its environment. Ultimately, the effects of the propellant slosh on the attitude stability and pointing performance of the entire spacecraft are of great interest to attitude control engineers. Equivalent mechanical models, such as models that approximate the fluid slosh effects by analogy to the movements of a point-mass pendulum, are important tools in simulating propellant slosh dynamics as part of the entire attitude determination and control system. This paper describes some of the current methods used to analyze and model slosh. It focuses on equivalent mechanical models and their incorporation into control-based analysis tools such as Simulink. The SDO mission is used as the case study for this work.
In this paper we present a simulation tool that has been used to develop an architecture for a low-cost Position, Navigation and Time (PNT) system to provide PNT services on and around the Moon using non-dedicated low-cost orbital and ground assets. The simulation tool has been developed to be flexible and is capable of modeling and analyzing the many different capabilities and configurations that the non-dedicated assets could support. The tool models the creation of an ad hoc swarm, the localization of this swarm and the subsequent provision of PNT services from this swarm. We present results from several studies of select configurations chosen to reflect existing and future real-world needs and capabilities. Over the next few decades there is expected to be a substantial increase in Lunar missions supporting and inspired by NASA’s Artemis Program. It is expected that a large fraction of these missions will be low cost, utilizing rideshares and CubeSats, just as has seen in Earth orbit over the past decade. Many of these missions will need navigation capabilities but may be unable to support the large power, mass and weight that a weak GNSS or DSN based navigation solution would entail. As Lunar PNT service demand is not likely to be needed over the entire lunar surface 24/7, the creation of a dedicated Lunar GNSS constellation cannot be justified. Hence, our proposed architecture envisions utilizing existing Lunar science and exploration assets to create ad hoc and on demand Lunar PNT swarms capable of providing PNT services to low cost missions. The simulation reflects the two distinct parts of the architecture: the creation of a Lunar PNT swarm using non-dedicated existing assets, and the quantitative modeling of the quality of the PNT services that this swarm provides. To support the former, the simulation supports various swarm localization techniques, including centralized and distributed EKFs both of which support pluggable dynamics models. In modeling the PNT service performance the simulation adopts standard techniques from the GNSS community, including providing degree of precision (DOP) estimates for theoretical end users. Crucially, all asset capabilities, including clock accuracy, independent location self-knowledge and timing measurement precision can be set independently for each asset, reflecting the key concept of utilizing non-dedicated assets. The simulation is predominantly implemented in MATLAB, with GMAT being used for the propagation of orbital assets. The paper will present results from the simulation reflecting the tool’s flexibility and focusing on scenarios that match real-world proposed missions, including scenarios designed to provide PNT support to lunar surface missions similar to NASA Ames' forthcoming VIPER mission. The performance of centralized and decentralized swarm configuration and localization techniques will be compared. Finally, performance of the PNT service provided by an autonomous Lunar PNT swarm will be compared to existing radiometric and weak GNSS methods.
Efforts to make increasingly use of suitable computer programs in the design of hardware have the potential to reduce expenditures. In this context, NASA has evaluated the benefits provided by software tools through an application to the Environmental Control and Life Support (ECLS) system. The present paper is concerned with the benefits obtained by an employment of simulation tools in the case of the Air Revitalization System (ARS) of a Space Station life support system. Attention is given to the ARS functions and components, a computer program overview, a SAND (solid amine water desorbed) bed model description, a model validation, and details regarding the simulation benefits.
This report focuses on efforts to improve Multiphysics Object-Oriented Simulation Environ-ment (MOOSE) for mechanical property evaluation using data analytics. These efforts involveimprovements to the stochastic tools module (STM) for stochastic simulations of MOOSE mul-tiphysics model and the development of inverse optimization capabilities. The report gives anoverview of the STM and describes recent updates to its core capabilities and theory on itsreduced-order model (ROM) schemes. Examples are also provided showing the impact of theseupdates and exhibits the usefulness of ROMs. An overview of the gradient based inverse opti-mziation algorithms are given along with examples of their application to source identification.Inverse optimization will provide a new methodology in STM for fitting model parameters toexperimental data.