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DOE OSTI2021

Designing Sequence-Defined Peptoids for Biomimetic Control over Inorganic Crystallization

Crystallization defines what the world is all about, ranging from biomineralization in living organisms to various materials in our lives. During these processes, biomineralization set a superexcellent example of the additive-controlled crystallization. However, the high complexity and low stability of peptides and proteins preclude their wide applications in controlling inorganic crystallization beyond the biological systems. Peptoids are one type of sequence-defined biomimetic polymers with a simple structure, high stability, protein-like molecular recognition, and distinctive self-assembly properties. They provide a promising alternative to mimic peptides and proteins for controlling inorganic crystallization and extend its application to predictive materials synthesis. In this review article, we extract the main concepts of peptoid engineering and highlight the recent advances in peptoid-controlled inorganic crystallization. Our focus is to understand the principles of sequence engineering that lead to the predictable physiochemical properties of these substances, which will give insights into other inorganic systems.

36 MATERIALS SCIENCE↗

NASA NTRS1986

Flight research on natural laminar flow nacelles - A progress report

This paper presents a progress report on an ongoing flight experiment for natural laminar flow nacelles. The results given herein were obtained during the first phase of the experiment, in which an instrumented natural laminar flow nacelle fairing was flight tested in the presence of turbofan engine noise and a controlled noise source. The results indicate that with the controlled noise source off, natural laminar flow was measured as far aft as 37 percent of the fairing length. The transition front was irregular in contour, and the extent of natural laminar flow was significantly affected by the relative flow angle for the fairing. In addition to these test results, the paper discusses the results of some recent computational analyses to predict pressure distributions and transition location, and to explain some of the data trends. Comparisons between measured and predicted data indicate that the analytical methods successfully predicted trends for the baseline (no controlled noise source) studies.

Hastings, E. C., Jr.↗

NASA NTRS2015

Inflight Characterization of the Cassini Spacecraft Propellant Slosh and Structural Frequencies

While there has been extensive theoretical and analytical research regarding the characterization of spacecraft propellant slosh and structural frequencies, there have been limited studies to compare the analytical predictions with measured flight data. This paper uses flight telemetry from the Cassini spacecraft to get estimates of high-g propellant slosh frequencies and the magnetometer boom frequency characteristics, and compares these values with those predicted by theoretical works. Most Cassini attitude control data are available at a telemetry frequency of 0.5 Hz. Moreover, liquid sloshing is attenuated by propellant management device and attitude controllers. Identification of slosh and structural frequency are made on a best-effort basis. This paper reviews the analytical approaches that were used to predict the Cassini propellant slosh frequencies. The predicted frequencies are then compared with those estimated using telemetry from selected Cassini burns where propellant sloshing was observed (such as the Saturn Orbit Insertion burn). Determination of the magnetometer boom structural frequency is also discussed.

Lee, Allan Y.↗

NASA NTRS2015

Inflight Characterization of the Cassini Spacecraft Propellant Slosh and Structural Frequencies

Lee, Allan Y.↗

NASA NTRS2002

The Current Status of Unsteady CFD Approaches for Aerodynamic Flow Control

An overview of the current status of time dependent algorithms is presented. Special attention is given to algorithms used to predict fluid actuator flows, as well as other active and passive flow control devices. Capabilities for the next decade are predicted, and principal impediments to the progress of time-dependent algorithms are identified.

Carpenter, Mark H.↗

NASA NTRS2004

Synthetic Jet Flow Field Database for CFD Validation

An oscillatory zero net mass flow jet was generated by a cavity-pumping device, namely a synthetic jet actuator. This basic oscillating jet flow field was selected as the first of the three test cases for the Langley workshop on CFD Validation of Synthetic Jets and Turbulent Separation Control. The purpose of this workshop was to assess the current CFD capabilities to predict unsteady flow fields of synthetic jets and separation control. This paper describes the characteristics and flow field database of a synthetic jet in a quiescent fluid. In this experiment, Particle Image Velocimetry (PIV), Laser Doppler Velocimetry (LDV), and hot-wire anemometry were used to measure the jet velocity field. In addition, the actuator operating parameters including diaphragm displacement, internal cavity pressure, and internal cavity temperature were also documented to provide boundary conditions for CFD modeling.

Yao, Chung-Sheng↗

NASA NTRS2015

Active Aerodynamic Load Reduction on a Rotorcraft Fuselage With Rotor Effects: A CFD Validation Effort

A rotorcraft fuselage is typically designed with an emphasis on operational functionality with aerodynamic efficiency being of secondary importance. This results in a significant amount of drag during high-speed forward flight that can be a limiting factor for future high-speed rotorcraft designs. To enable higher speed flight, while maintaining a functional fuselage design (i.e., a large rear cargo ramp door), the NASA Rotary Wing Project has conducted both experimental and computational investigations to assess active flow control as an enabling technology for fuselage drag reduction. This paper will evaluate numerical simulations of a flow control system on a generic rotorcraft fuselage with a rotor in forward flight using OVERFLOW, a structured mesh Reynolds-averaged Navier-Stokes flow solver developed at NASA. The results are compared to fuselage forces, surface pressures, and PN flow field data obtained in a wind tunnel experiment conducted at the NASA Langley 14-by 22-Foot Subsonic Tunnel where significant drag and download reductions were demonstrated using flow control. This comparison showed that the Reynolds-averaged Navier-Stokes flow solver was unable to predict the fuselage forces and pressure measurements on the ramp for the baseline and flow control cases. While the CFD was able to capture the flow features, it was unable to accurately predict the performance of the flow control.

Allan, Brian G.↗

NASA NTRS2018

Airspace Technology Demonstration 2 (ATD-2) Phase 1 Concept of Use (ConUse)

This document presents an operational Concept of Use (ConUse) for the Phase 1 Baseline Integrated Arrival, Departure, and Surface (IADS) prototype system of NASA's Airspace Technology Demonstration 2 (ATD-2) sub-project, which began demonstration in 2017 at Charlotte Douglas International Airport (CLT). NASA is developing the IADS system under the ATD-2 sub-project in coordination with the Federal Aviation Administration (FAA) and aviation industry partners. The primary goal of ATD-2 sub-project is to improve the predictability and the operational efficiency of the air traffic system in metroplex environments, through the enhancement, development, and integration of the nation's most advanced and sophisticated arrival, departure, and surface prediction, scheduling, and management systems. The ATD-2 effort is a five-year research activity through 2020. The initial phase of the ATD-2 sub-project, which is the focus of this document, will demonstrate the Phase 1 Baseline IADS capability at CLT in 2017. The Phase 1 Baseline IADS capabilities of the ATD-2 sub-project consists of: (a) Strategic and tactical surface scheduling to improve efficiency and predictability of airport surface operations, (b) Tactical departure scheduling to enhance merging of departures into overhead traffic streams via accurate predictions of takeoff times and automated coordination between the Airport Traffic Control Tower (ATCT, or Tower) and the Air Route Traffic Control Center (ARTCC, or Center), (c) Improvements in departure surface demand predictions in Time Based Flow Management (TBFM), (d) A prototype Electronic Flight Data (EFD) system provided by the FAA via the Terminal Flight Data Manager (TFDM) early implementation effort, and (e) Improved situational awareness and demand predictions through integration with the Traffic Flow Management System (TFMS), TBFM, and TFDM (3Ts) for electronic data integration and exchange, and an on-screen dashboard displaying pertinent analytics in real-time. The surface scheduling and metering element of the capability is consistent with the Surface CDM Concept of Operations published in 2014 by the FAA Surface Operations Directorate.1 Upon successful demonstration of the Phase 1 Baseline IADS capability, follow-on demonstrations of the matured IADS traffic management capabilities will be conducted in the 2018-2020 timeframe. At the end of each phase of the demonstrations, NASA will transfer the ATD-2 sub-project technology to the FAA and industry partners.

integrated arrival↗

NASA NTRS1983

Satellite freeze forecast system: Executive summary

A satellite-based temperature monitoring and prediction system consisting of a computer controlled acquisition, processing, and display system and the ten automated weather stations called by that computer was developed and transferred to the national weather service. This satellite freeze forecasting system (SFFS) acquires satellite data from either one of two sources, surface data from 10 sites, displays the observed data in the form of color-coded thermal maps and in tables of automated weather station temperatures, computes predicted thermal maps when requested and displays such maps either automatically or manually, archives the data acquired, and makes comparisons with historical data. Except for the last function, SFFS handles these tasks in a highly automated fashion if the user so directs. The predicted thermal maps are the result of two models, one a physical energy budget of the soil and atmosphere interface and the other a statistical relationship between the sites at which the physical model predicts temperatures and each of the pixels of the satellite thermal map.

Martsolf, J. D.↗

NASA NTRS1991

Rotor and control system loads analysis of the XV-15 with the advanced technology blades

An analysis of the rotor and control system loads of the XV-15 with the Advanced Technology Blades (XV-15/ATB) was conducted to study the effects of modifications designed to alleviate high collective actuator loads encountered during initial flight tests. Rotor loads predictions were correlated with flight data to establish accuracies of the methodology used in the analysis. Control system loads predictions were then examined and were also correlated with flight data. The results showed a significant reduction in 3/rev collective actuator loads of the XV-15/ATB when the control system stiffness was increased and the rotor blade chord balance and tip twist were modified.

Totah, Joseph J.↗

NASA NTRS1990

Rotor and control system loads analysis of the XV-15 with the advanced technology blades

An analysis of the rotor and control system loads of the XV-15 with the Advanced Technology Blades (XV-15/ATB) was conducted to investigate the effects of modifications designed to alleviate high collective actuator loads encountered during initial flight tests. Rotor loads predictions were correlated with flight data to establish accuracies of the methodology used in the analysis. Control system loads predictions were then examined and were also correlated with flight data. The results showed a significant reduction in 3/rev collective actuator loads of the XV-15/ATB when the control system stiffness was increased and the rotor blade chord balance and tip twist were modified.

Totah, Joseph J.↗

DOE OSTI2020

A Phenomenological Model for Cavitation

A phenomenological model of cavitation is presented, based on observations that both large relative negative pressures and large negative time derivatives of pressure are required for cavitation onset. We simulated two cavitation experiments to generate cavitation scaling parameters for relative pressure drop and rate of pressure drop. Our results show the model, while simple, is effective at reproducing results from laboratory experiments of cavitation. The parameters were then used in conjunction with a human surrogate computational model to predict, at any position within the head, the probability of intracranial cavitation caused by exposure to a blast event. The results suggest that the magnitude of blast overpressure observed in field data is sufficient to cause intracranial cavitation. Our analysis indicates that the helmeted head, when compared to the unhelmeted head configuration, results in a decrease but not elimination of cavitation exposure. When density functions of cavitation probability versus cumulative brain volume are combined with an injury severity model, the results show helmet efficacy at low and moderate risk levels. However, the convergence of unhelmeted and helmeted probability density functions at high-to-excessive risk thresholds indicates the helmet offers diminishing protection at elevated exposure levels, relative to the unhelmeted baseline. Future investigation and collaboration with neuroscience subject matter experts are needed to contextualize the current computational results. While the present work contributes specific and quantified predictions of intracranial cavitation location and severity, more research is required to apply our results to clinical settings with population-based brain injury subjects and controls. The relationship between our intracranial cavitation predictions with their anticipated clinical sequelae remains a topic in need of exploration.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Autonomous convergence of STM control parameters using Bayesian optimization

Scanning tunneling microscopy (STM) is a widely used tool for atomic imaging of novel materials and their surface energetics. However, the optimization of the imaging conditions is a tedious process due to the extremely sensitive tip–surface interaction, thus limiting the throughput efficiency. In this paper, we deploy a machine learning (ML)-based framework to achieve optimal atomically resolved imaging conditions in real time. The experimental workflow leverages the Bayesian optimization (BO) method to rapidly improve the image quality, defined by the peak intensity in the Fourier space. The outcome of the BO prediction is incorporated into the microscope controls, i.e., the current setpoint and the tip bias, to dynamically improve the STM scan conditions. We present strategies to either selectively explore or exploit across the parameter space. As a result, suitable policies are developed for autonomous convergence of the control parameters. The ML-based framework serves as a general workflow methodology across a wide range of materials.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS1991

Modal truncation, Ritz vectors, and derivatives of closed-loop damping ratios

The effect of modal truncation on the damping ratio and their derivatives with respect to an added mass is investigated for a simply supported, multispan beam with a linear quadratic Gaussian control system. It is found that both the damping ratios and derivatives converge slowly, but the derivatives converge more slowly than the damping ratios. However, it is shown that when Ritz vectors corresponding to static displacements due to actuator forces are added to the reduced model, the convergence of both the damping ratios and their derivatives is accelerated. It is also shown that the accuracy of the damping ratio predicted by a reduced-model control design can be improved significantly if the Ritz vectors are included in the design of the control system. Thus, it appears that Ritz vectors added to the reduced model of flexible structures can improve greatly the accuracy of both the design and analysis of the control system.

Sandridge, Chris A.↗

DOE OSTI2024

Geophysical Imaging of Flow and Transport (GIFT): FY24 Status Report

The GIFT (Geophysical Imaging of Flow and Transport) system will improve predictive capabilities as a platform for collecting multi-physical (MP) time-lapse datasets from well-controlled laboratory experiments. This will enable more accurate prediction of multi-phase fluid flow during delivery and transport of insitu remedial amendments as important components of the overall Hanford Site cleanup mission. Design and construction of the GIFT system, which consists of a meter-scale test cell and a network of custom gas circulation and analysis systems, was accomplished in fiscal year (FY) 2024, with plans to add liquid circulation to the system and use this new capability for multi-phase deep vadose experiments starting in FY25.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1993

Validated technology for the reduction of spacecraft vibrations - Controls-Structures Integration (CSI)

The NASA Langley Research Center has constructed several testbeds to assess the viability of flexible structure control. It is found, however, that simply adding sensors, actuators, and a control system to an existing structure (i.e. space platform) is not the preferred methodology for improving pointing performance. When the structure is designed without regard to pointing control, significant design freedom is lost. The preferred design procedure is to simultaneously design the structure and the control system, hence, the name Controls-Structures Integration. By designing the structure and control system simultaneously, much higher efficiency can be achieved. In this study, an 18 m long truss structure with several appendages was enhanced through integrated controls and structures design. The design was fabricated and tested for validation of the methodology. Test results collaborated predictions and showed a 60 percent reduction in control energy for the enhanced test article.

Newsom, Jerry R.↗

DOE OSTI2022

Release Timing and Duration Control the Fate of Photolytic Compounds in Stream-Hyporheic Systems

Predicting environmental fate requires an understanding of the underlying, spatiotemporally variable interaction of transport and transformation processes. Photolytic compounds, for example, interact with both time-variable photolysis and the perennially dark hyporheic zone, generating potentially unexpected dynamics that arise from time-variable reactivity. This interaction has been found to significantly impact environmental fate but is commonly oversimplified in predictive models. Our primary objective was to explore how time-variable photolysis and hyporheic storage interact across a range of photolysis rates to control the fate and transport of photolytic solutes in stream-hyporheic systems. In this study, we released a photolytic compound in a natural system at different times of day and simulated variable release timing and durations of photolytic compounds spanning half-lives ranging from about 2 min to 900 hr. To contextualize these results, we simulated five photolytic compounds with varied half-lives to systematically study the interaction between release timing, duration, and reactivity. We found that the environmental fate and transport of photolytic compounds are highly variable as a function of release timing, which controls when, where, and for how long solute is stored in the hyporheic zone or exposed to in-channel photolysis. Finally, this knowledge can be used to improve predictions for photolytic compounds or assess potential impacts for an anticipated discharge or treatment.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1991

An architecture for designing fuzzy logic controllers using neural networks

Described here is an architecture for designing fuzzy controllers through a hierarchical process of control rule acquisition and by using special classes of neural network learning techniques. A new method for learning to refine a fuzzy logic controller is introduced. A reinforcement learning technique is used in conjunction with a multi-layer neural network model of a fuzzy controller. The model learns by updating its prediction of the plant's behavior and is related to the Sutton's Temporal Difference (TD) method. The method proposed here has the advantage of using the control knowledge of an experienced operator and fine-tuning it through the process of learning. The approach is applied to a cart-pole balancing system.

Berenji, Hamid R.↗