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NASA NTRS1995

User manual for NASA Lewis 10 by 10 foot supersonic wind tunnel

This manual describes the 10- by 10-Foot Supersonic Wind Tunnel at the NASA Lewis Research Center and provides information for users who wish to conduct experiments in this facility. Tunnel performance operating envelopes of altitude, dynamic pressure, Reynolds number, total pressure, and total temperature as a function of test section Mach number are presented. Operating envelopes are shown for both the aerodynamic (closed) cycle and the propulsion (open) cycle. The tunnel test section Mach number range is 2.0 to 3.5. General support systems, such as air systems, hydraulic system, hydrogen system, fuel system, and Schlieren system, are described. Instrumentation and data processing and acquisition systems are also described. Pretest meeting formats and schedules are outlined. Tunnel user responsibility and personnel safety are also discussed.

Soeder, Ronald H.↗

NASA NTRS1996

Mission simulation as an approach to develop requirements for automation in Advanced Life Support Systems

This paper examines mission simulation as an approach to develop requirements for automation and robotics for Advanced Life Support Systems (ALSS). The focus is on requirements and applications for command and control, control and monitoring, situation assessment and response, diagnosis and recovery, adaptive planning and scheduling, and other automation applications in addition to mechanized equipment and robotics applications to reduce the excessive human labor requirements to operate and maintain an ALSS. Based on principles of systems engineering, an approach is proposed to assess requirements for automation and robotics using mission simulation tools. First, the story of a simulated mission is defined in terms of processes with attendant types of resources needed, including options for use of automation and robotic systems. Next, systems dynamics models are used in simulation to reveal the implications for selected resource allocation schemes in terms of resources required to complete operational tasks. The simulations not only help establish ALSS design criteria, but also may offer guidance to ALSS research efforts by identifying gaps in knowledge about procedures and/or biophysical processes. Simulations of a planned one-year mission with 4 crewmembers in a Human Rated Test Facility are presented as an approach to evaluation of mission feasibility and definition of automation and robotics requirements.

NASA Discipline Number 61-10↗

DOE OSTI2017

Grid site availability evaluation and monitoring at CMS

The Compact Muon Solenoid (CMS) experiment at the Large Hadron Collider (LHC) uses distributed grid computing to store, process, and analyse the vast quantity of scientific data recorded every year. The computing resources are grouped into sites and organized in a tiered structure. Each site provides computing and storage to the CMS computing grid. Over a hundred sites worldwide contribute with resources from hundred to well over ten thousand computing cores and storage from tens of TBytes to tens of PBytes. In such a large computing setup scheduled and unscheduled outages occur continually and are not allowed to significantly impact data handling, processing, and analysis. Unscheduled capacity and performance reductions need to be detected promptly and corrected. CMS developed a sophisticated site evaluation and monitoring system for Run 1 of the LHC based on tools of the Worldwide LHC Computing Grid. For Run 2 of the LHC the site evaluation and monitoring system is being overhauled to enable faster detection/reaction to failures and a more dynamic handling of computing resources. Furthermore, enhancements to better distinguish site from central service issues and to make evaluations more transparent and informative to site support staff are planned.

43 PARTICLE ACCELERATORS↗

NASA NTRS1993

Nonlinear dynamic simulation of single- and multi-spool core engines

In this paper a new computational method for accurate simulation of the nonlinear dynamic behavior of single- and multi-spool core engines, turbofan engines, and power generation gas turbine engines is presented. In order to perform the simulation, a modularly structured computer code has been developed which includes individual mathematical modules representing various engine components. The generic structure of the code enables the dynamic simulation of arbitrary engine configurations ranging from single-spool thrust generation to multi-spool thrust/power generation engines under adverse dynamic operating conditions. For precise simulation of turbine and compressor components, row-by-row calculation procedures were implemented that account for the specific turbine and compressor cascade and blade geometry and characteristics. The dynamic behavior of the subject engine is calculated by solving a number of systems of partial differential equations, which describe the unsteady behavior of the individual components. In order to ensure the capability, accuracy, robustness, and reliability of the code, comprehensive critical performance assessment and validation tests were performed. As representatives, three different transient cases with single- and multi-spool thrust and power generation engines were simulated. The transient cases range from operating with a prescribed fuel schedule, to extreme load changes, to generator and turbine shut down.

Schobeiri, T.↗

NASA NTRS2012

First Assessments of Predicted ICESat-2 Performance Using Aircraft Data

The Ice, Cloud, and land Elevation Satellite-2 (ICESat-2) is a next-generation laser altimeter designed to continue key observations of ice sheet elevation change, sea ice freeboard, vegetation canopy height, earth surface elevation, and sea surface height. Scheduled for launch in mid-2016, ICESat-2 will use a high repetition rate (10 kHz), small footprint (10 m nominal ground diameter) laser, and a single-photon-sensitive detection strategy (photon counting) to measure precise range to the earth's surface. Using green light (532 nm), the six beams of ICESat-2 will provide improved spatial coverage compared with the single beam of ICESat, while the differences in transmit energy among the beams provide a large dynamic range. The six beams are arranged into three pairs of beams which allow slopes to measured on an orbit-by-orbit basis. In order to evaluate models of predicted ICESat-2 performance and provide ICESat-2-like data for algorithm development, an airborne ICESat-2 simulator was developed and first flown in 2010. This simulator, the Multiple Altimeter Beam Experimental Lidar (MABEL) was most recently deployed to Iceland in April 2012 and collected approx 85 hours of science data over land ice, sea ice, and calibration targets. MABEL uses a similar photon-counting measurement strategy to what will be used on ICESat-2. MABEL collects data in 16 green channels and an additional 8 channels in the infrared aligned across the direction of flight. By using NASA's ER-2 aircraft flying at 20km altitude, MABEL flies as close to space as is practical, and collects data through approx 95% of the atmosphere. We present background on the MABEL instrument, and data from the April 2012 deployment to Iceland. Among the 13 MABEL flights, we collected data over the Greenland ice sheet interior and outlet glaciers in the southwest and western Greenland, sea ice data over the Nares Strait and Greenland Sea, and a number of small glaciers and ice caps in Iceland and Svalbard. Several of the flights were coincident in time and space with NASA's Operation IceBridge, which provides an independent data set for validation. MABEL also collected data along CryoSat track 10482 in north central Greenland approximately one month after CryoSat passed overhead.

Neumann, Thomas↗

NASA NTRS2012

SOFIA: Flying the Telescope

The primary focus of this paper is how the flight test team for the Stratospheric Observatory For Infrared Astronomy (SOFIA) re-cast an extensive developmental test program to meet key milestones while simultaneously ensuring safe certification of the airframe and delivery of an operationally relevant platform, ultimately saving the overall program from financial demise. Following a brief introduction to the observatory and what it is designed to do, SOFIAs planned developmental test program is summarized, including analysis and design philosophy, envelope expansion, model validation and airframe certification. How NASA used lessons learned from other aircraft that employed open cavities in flight is explained as well as how and why the chosen design was selected. The approach to aerodynamic analysis, including bare airframe testing, wind tunnel testing, computational fluid dynamics and finite element modeling proved absolutely critical. Despite a solid analytical foundation, many unknowns remained. History provides several examples of disastrous effects on both systems and flight safety if cavity design is not approached properly. For these reasons, an extensive test plan was developed to ensure a safe and thorough build-up for envelope expansion, airframe certification and early science missions. Unfortunately, as is often the case, because of chronic delays in overall program execution, severe schedule and funding pressures were present. If critical milestones were not met, domestic as well as international funding was in serious jeopardy, and the demise of the entire program loomed large. Concentrating on rigorous model validation, the test team challenged certification requirements, increased test efficiency and streamlined engineering analysis. This resulted in the safe reduction of test point count by 72%, meeting all program milestones and a platform that soundly satisfied all operational science requirements. Results from early science missions are shown and a proof of concept mission for which SOFIA was opportunely positioned is showcased. Success on this time-critical mission to observe a rare astronomical event proved the usefulness of an airborne observatory and the value in waiting for the capability provided by SOFIA. Finally, lessons learned in the test program are presented with emphasis on how lessons from previous aircraft and successful test programs were applied to SOFIA. Effective application of these lessons was crucial to the success of the SOFIA flight test program. SOFIA is an international cooperative program between NASA and the German Space Agency, DLR. It is a 2.5 meter (100-inch) telescope mounted in a Boeing 747SP aircraft used for astronomical observations at altitudes above 35,000 feet. SOFIA will accommodate a host of scientific instruments from the international science community and has a planned operational lifespan of more than 20 years.

Asher, Troy A.↗

NASA NTRS2011

Identifying Functional Requirements for Flexible Airspace Management Concept Using Human-In-The-Loop Simulations

Flexible Airspace Management (FAM) is a mid- term Next Generation Air Transportation System (NextGen) concept that allows dynamic changes to airspace configurations to meet the changes in the traffic demand. A series of human-in-the-loop (HITL) studies have identified procedures and decision support requirements needed to implement FAM. This paper outlines a suggested FAM procedure and associated decision support functionality based on these HITL studies. A description of both the tools used to support the HITLs and the planned NextGen technologies available in the mid-term are presented and compared. The mid-term implementation of several NextGen capabilities, specifically, upgrades to the Traffic Management Unit (TMU), the initial release of an en route automation system, the deployment of a digital data communication system, a more flexible voice communications network, and the introduction of a tool envisioned to manage and coordinate networked ground systems can support the implementation of the FAM concept. Because of the variability in the overall deployment schedule of the mid-term NextGen capabilities, the dependency of the individual NextGen capabilities are examined to determine their impact on a mid-term implementation of FAM. A cursory review of the different technologies suggests that new functionality slated for the new en route automation system is a critical enabling technology for FAM, as well as the functionality to manage and coordinate networked ground systems. Upgrades to the TMU are less critical but important nonetheless for FAM to be fully realized. Flexible voice communications network and digital data communication system could allow more flexible FAM operations but they are not as essential.

dynamic airspace configuration↗

DOE OSTI2023

Deployment of Dynamic Neural Network Optimization to Minimize Heat Rate During Ramping for Coal Power Plants (Final Technical Report)

Much success was achieved throughout the course of this project. A successful implementation of Dynamic Neural Network Optimization (D-NNO) was coupled with Adaptive Predictive Controls (APC) and a novel hardware installation comprised of an advanced sensor network (ASN) measuring mass-weighted averages of flue gas constituents above the horizontal superheater of a coal-fired utility boiler. From 2019 through 2023 (including an extension due to COVID delays), the team was able to prototype, evaluate, deploy, iterate, and ultimately finalize an advanced closed-loop control D-NNO system which demonstrated the ability to: •improve unit efficiency ~2.0% relative to unoptimized operation (represented as total fuel fired per MWh generated) •improve unit NOx emission rates 10%+ beyond static optimization baselines •improve unit temperature stability as much as 58% and on average 12% •improve operating load stability as much as 35% The culmination of this project has generated an advanced methodology of deploying specially designed recurrent neural networks (long short-term memory, gated recurrent unit, encoder-decoder networks, transformers, etc.), customized trajectory planning and closed-loop optimization modules capable of adapting to live electric grid responses and demands, self-tuning and adaptive expert controls constantly adjusting prediction parameters to real-time unit behavior, and a hardware/software package able to reliably calculate net unit heat rate (NUHR) in real-time using flue gas constituents, machine learning, and known combustion relationships. Through this real-time NUHR value, immediate feedback on system adjustments relative to operating efficiency was available, allowing for rapid improvements to system performance. In addition to development and deployment of the advanced D-NNO system, the approach methodology has been readily commercialized through the project platform Griffin Open Systems, LLC, the D-NNO software platform host. Similar methodologies to those developed by this project have already been deployed at 5 other units across the United States, with another 6 implementations scheduled, and more expected. Over the course of the project, multiple academic papers were submitted and accepted for publication within esteemed academic journals, and PhD students were trained and graduated, as well as undergraduate students becoming involved and participating to project objectives.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Extreme-scale stochastic optimization and simulation via learning-enhanced decomposition and parallelization (Final Technical Report)

Stochastic optimization and simulation models ubiquitously arise in designing and operating complex service/engineering systems. They can be extreme in scale due to high-dimensional data and decisions, and can also involve decisions made sequentially in response to newly revealed data, both causing significant computational challenge. The objective of this research is to explore a unified framework that integrates machine learning with discrete optimization and risk-averse modeling, to improve the efficiency of decomposition paradigms for stochastic optimization and simulations at extreme scale. The models we consider represent a broad class of complex decision-making problems, where 0-1 or continuous decisions are made before and/or after knowing multiple sources of uncertainties that could be correlated. We will employ machine learning methods to dynamically decide and prioritize computational procedures, including cut generation, branching, and bounding of the optimal objective. Furthermore, the research will shed new lights on the traditional decomposition algorithms for extreme-scale computing. Deliverables of the research include new modeling and computational methods for advancing the state-of-the-art research in optimization and simulation, bringing many relevant risk-averse, data-driven optimization problems in practice within the range of tractability. Examples include distributed computing server scheduling and sensor deployment for monitoring critical infrastructures. Success in this effort will enable progress in solving multiple extreme-scale problems in the complex system design and operations arising from DoE missions in energy, environment, and national security.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1992

The internal dynamics of slowly rotating biological systems

The structure and the dynamics of biological systems are complex. Steady gravitational forces that act on organisms cause hydrostatic pressure gradients, stress in solid components, and ordering of movable subsystems according to density. Rotation induces internal motion; it also stresses and or deforms regions of attachment and containment. The disrupted gravitationally ordered layers of movable entities are replaced by their orbital movements. New ordering geometries may arise also, especially if fluids of various densities occur. One novel result obtained concerns the application of scheduled variation of clinostat rotation rates to the management of intracellular particle trajectories. Rotation and its consequences are discussed in terms of scaling factors for parameters such as time, derived from mathematical models for simple rotating mechanical systems.

Kessler, John O.↗

NASA NTRS1997

Constrained Multipoint Aerodynamic Shape Optimization Using an Adjoint Formulation and Parallel Computers

An aerodynamic shape optimization method that treats the design of complex aircraft configurations subject to high fidelity computational fluid dynamics (CFD), geometric constraints and multiple design points is described. The design process will be greatly accelerated through the use of both control theory and distributed memory computer architectures. Control theory is employed to derive the adjoint differential equations whose solution allows for the evaluation of design gradient information at a fraction of the computational cost required by previous design methods. The resulting problem is implemented on parallel distributed memory architectures using a domain decomposition approach, an optimized communication schedule, and the MPI (Message Passing Interface) standard for portability and efficiency. The final result achieves very rapid aerodynamic design based on a higher order CFD method. In order to facilitate the integration of these high fidelity CFD approaches into future multi-disciplinary optimization (NW) applications, new methods must be developed which are capable of simultaneously addressing complex geometries, multiple objective functions, and geometric design constraints. In our earlier studies, we coupled the adjoint based design formulations with unconstrained optimization algorithms and showed that the approach was effective for the aerodynamic design of airfoils, wings, wing-bodies, and complex aircraft configurations. In many of the results presented in these earlier works, geometric constraints were satisfied either by a projection into feasible space or by posing the design space parameterization such that it automatically satisfied constraints. Furthermore, with the exception of reference 9 where the second author initially explored the use of multipoint design in conjunction with adjoint formulations, our earlier works have focused on single point design efforts. Here we demonstrate that the same methodology may be extended to treat complete configuration designs subject to multiple design points and geometric constraints. Examples are presented for both transonic and supersonic configurations ranging from wing alone designs to complex configuration designs involving wing, fuselage, nacelles and pylons.

Reuther, James↗

DOE OSTI2017

GPU-accelerated red blood cells simulations with transport dissipative particle dynamics

Mesoscopic numerical simulations provide a unique approach for the quantification of the chemical influences on red blood cell functionalities. The transport Dissipative Particle Dynamics (tDPD) method can lead to such effective multiscale simulations due to its ability to simultaneously capture mesoscopic advection, diffusion, and reaction. In this paper, we present a GPU-accelerated red blood cell simulation package based on a tDPD adaptation of our red blood cell model, which can correctly recover the cell membrane viscosity, elasticity, bending stiffness, and cross-membrane chemical transport. The package essentially processes all computational workloads in parallel by GPU, and it incorporates multi-stream scheduling and non-blocking MPI communications to improve inter-node scalability. Our code is validated for accuracy and compared against the CPU counterpart for speed. Strong scaling and weak scaling are also presented to characterize scalability. We observe a speedup of on one GPU over all cores within a single node, and a weak scaling efficiency of across nodes. The program enables quick-turnaround and high-throughput numerical simulations for investigating chemical-driven red blood cell phenomena and disorders.

Computer Science↗

DOE OSTI2022

A Novel Grid-forming Voltage Control Strategy for Supplying Unbalanced Microgrid Loads Using Inverter-based Resources

This paper presents a novel grid-forming voltage control strategy for a battery energy storage system to maintain balanced three-phase output voltages when serving unbalanced loads. A stationary reference frame (αβ) based control scheme is proposed to regulate positive-sequence and negative-sequence voltages. Compared with the conventional rotating reference frame (dq) based control scheme, the proposed scheme shows better dynamic performance. Then, we analyze the system zero-sequence network and propose adding a grounding transformer to the Y/Yg connected output transformer to further reduce the voltage unbalance at the point of common coupling. The simulation results demonstrate the effective performance of the proposed voltage control scheme. Based on the results, the power-voltage unbalance curve is derived for different output transformer configurations to establish the relationship between the power unbalance limit and the voltage unbalance limit for microgrid power scheduling.

Xu, Bei↗

DOE OSTI2019

Stackelberg Game Based on Supervised Charging Method and Pricing Strategy of Charging Service Providers

The charging of large-scale electric vehicles (EVs) brings about a large new load to the electricity network, while it is also a demand response resource. Smart charging equipment and patterns of charging service will be one of the research focuses at the next stage. Smart charging equipment schedules EV's charging on the basis of electricity price, and this method enables users to hold the right of controlling their own EV's charging procedure. Thus, there exists a Stackelberg game between charging service providers, who set the price, and independent EVs. The marginal charging price, which reflects properties of individual EV, and the pricing strategy of charging service providers can be derived through solving this game problem. A price based charging strategy is proposed, which is suitable for the dynamic electricity price mechanism because of its light communication burden. In a simulation of a charging service provider covering 200 smart devices, this real-time supervised charging strategy shows its advantages of curbing users' payment and guiding the charging load effectively.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2018

6DOF Testing of the SLS Inertial Navigation Unit

The Navigation System on the NASA Space Launch System (SLS) Block 1 vehicle performs initial alignment of the Inertial Navigation System (INS) navigation frame through gyrocompass alignment (GCA). Because the navigation architecture for the SLS Block 1 vehicle is a purely inertial system, the accuracy of the achieved orbit relative to mission requirements is very sensitive to initial alignment accuracy. The assessment of this sensitivity and many others via simulation is a part of the SLS Model-Based Design and Model-Based Requirements approach. As a part of the aforementioned, 6DOF Monte Carlo simulation is used in large part to develop and demonstrate verification of program requirements. To facilitate this and the GN&C flight software design process, an SLS-Program-controlled Design Math Model (DMM) of the SLS INS was developed by the SLS Navigation Team. The SLS INS model implements all of the key functions of the hardware-namely, GCA, inertial navigation, and FDIR (Fault Detection, Isolation, and Recovery)-in support of SLS GN&C design requirements verification. Despite the strong sensitivity to initial alignment, GCA accuracy requirements were not verified by test due to program cost and schedule constraints. Instead, the system relies upon assessments performed using the SLS INS model. In order to verify SLS program requirements by analysis, the SLS INS model is verified and validated against flight hardware. In lieu of direct testing of GCA accuracy in support of requirement verification, the SLS Navigation Team proposed and conducted an engineering test to, among other things, validate the GCA performance and overall behavior of the SLS INS model through comparison with test data. This paper will detail dynamic hardware testing of the SLS INS, conducted by the SLS Navigation Team at Marshall Space Flight Center's 6DOF Table Facility, in support of GCA performance characterization and INS model validation. A 6-DOF motion platform was used to produce 6DOF pad twist and sway dynamics while a simulated SLS flight computer communicated with the INS. Tests conducted include an evaluation of GCA algorithm robustness to increasingly dynamic pad environments, an examination of GCA algorithm stability and accuracy over long durations, and a long-duration static test to gather enough data for Allan Variance analysis. Test setup, execution, and data analysis will be discussed, including analysis performed in support of SLS INS model validation.

Geohagan, Kevin↗

NASA NTRS2021

OSIRIS-REx Orbit Trim Strategy

One of the more challenging aspects of the trajectory design for the OSIRIS-REx (Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer) mission at asteroid Bennu was maneuvering while in orbit. The orbital dynamics were highly perturbed by various sources, most notably solar radiation pressure, which degraded accuracy of long term predictions of the spacecraft’s location in orbit. Generally, the Navigation team had to solve three separate issues: correcting a perturbed orbit, changing to a different orbit, or phasing the or bitto place the spacecraft at a specific location at a specific time. The team composed a common framework using up to two maneuvers that could solve all of these problems using an identical schedule that allowed for consistent planning long before the final trajectory could be designed. This orbit trim strategy was successfully used for the first time in the Orbital B phase of the mission to maximize the duration of usable observing geometry in a time-variable orbit with strict operational limits. It was used an additional 3 times throughout the mission to adjust and/or change the orbit, most notably altering the orbit in the weeks prior to the successful Touch-And-Go (TAG)sample collection attempt. This same strategy was used to phase the orbit a total 10 times in preparation for each of the science sorties over potential sample sites, the TAG Rehearsals, and TAG. The trim strategy was demonstrated to be robust and performed exceptionally well in all aspects, which proved critical to a successful sample collection.

Daniel R. Wibben↗

NASA NTRSDate not supplied

SLS Payload Launch Loads Analysis Using the NTRC Method

Norton-Thevenin Receptance Coupling (NTRC), as described in several NASA Engineering and Safety Center (NESC) papers shows promise in enabling loads development for payloads with less computational cost and analyst time as compared to a full integrated vehicle coupled loads analysis (CLA). NTRC allows the free vehicle responses and impedance (accelerance) at the payload to vehicle interface (derived from integrated vehicle CLA) to be used with a payload model in a payload CLA. Due to the NTRC damping differing from the full integrated vehicle damping, results are slightly different, so coverage factors were developed to ensure NTRC results enveloped results from a traditional CLA. NTRC results with coverage factors were very close to full CLA results. The Space Launch System (SLS) coupled loads team has developed an implementation of the NTRC method to enable support of co-manifested payloads with analysis needs that do not fit the primary SLS load cycle schedule. The NTRC method was successfully used to support the European System Providing Refueling, Infrastructure, and Communications (ESPRIT) module for Gateway planned to fly on Artemis V and has been adopted as the SLS approach for supporting payload CLA requests that do not align with vehicle load cycles.

SLS↗

NASA NTRSDate not supplied

Application of Norton-Thevenin Receptance Coupling (NTRC) to Space Launch System (SLS) Payload Coupled Loads Analysis (CLA)

SLS↗