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DOE OSTI2019

Identification of Critical Surface Parameters Driving Lectin-Mediated Capture of Bacteria from Solution

Lectin-functional interfaces are useful for isolation of bacteria from solution because they are low-cost and allow nondestructive, reversible capture. This study provides a systematic investigation of physical and chemical surface parameters that influence bacteria capture over lectin-functionalized polymer interfaces and then applies these findings to construct surfaces with significantly enhanced bacteria capture. The designer block copolymer poly(glycidyl methacrylate)-block-poly(vinyldimethyl azlactone) was used as a lectin attachment layer, and lectin coupling into the polymer film through azlactone–lectin coupling reactions was first characterized. Here, experimental parameters including polymer areal chain density, lectin molecular weight, and lectin coupling buffer were systematically varied to identify parameters driving highest azlactone conversions and corresponding lectin surface densities. To introduce physical nanostructures into the attachment layer, nanopillar arrays (NPAs) of varied heights (300 and 2100 nm) were then used to provide an underlying surface template for the functional polymer layer. Capture of Escherichia coli on lectin–polymer surfaces coated over both flat and NPA surfaces was then investigated. For flat polymer interfaces, bacteria were detected on the surface after incubation at a solution concentration of 10 3 cfu/mL, and a corresponding detection limit of 1.7 × 10 3 cfu/mL was quantified. This detection limit was 1 order of magnitude lower than control lectin surfaces functionalized with standard, carbodiimide coupling chemistry. NPA surfaces containing 300 nm tall pillars further improved the detection limit to 2.1 × 10 2 cfu/mL, but also reduced the viability of captured cells. Finally, to investigate the impact of cell surface parameters on capture, we used Agrobacterium tumefaciens cells genetically modified to allow manipulation of exopolysaccharide adhesin production levels. Statistical analysis of surface capture levels revealed that lectin surface density was the primary factor driving capture, as opposed to exopolysaccharide adhesin expression. These findings emphasize the critical importance of the synthetic interface and the development of surfaces that combine high lectin densities with tailored physical features to drive high levels of capture. These insights will aid in design of biofunctional interfaces with physicochemical surface properties favorable for capture and isolation of bacteria cells from solutions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2011

Application of Kalman Filter to Improve Model Integrity for Securing Electricity Delivery

Power system model integrity is essential to many planning and operation tasks to ensure the safety and reliability of electricity delivery. Inaccurate system models would result in unreliable assessment of system security conditions and cause large-scale blackouts such as the 2003 Northeast Blackout. This dictates a strong need for model calibration and verification, which should be done periodically and preferably, in an automatic manner. Our previous work has demonstrated the feasibility of applying Extended Kalman Filter (EKF) to calibrate generator parameters using disturbance data recorded by phasor measurement units (PMU). This paper proposes to use Riccati equation to investigate EKF’s performance, especially regarding parameter identifiability. The covariance, which can be derived from the Riccati equation, offers insight into the uncertainties of parameters estimated by the EKF-based method. Simulation results show the effectiveness of the proposed approach.

calibration↗

NASA NTRS1976

Optimum data utilization for parameter identification with application to lifting rotors

The work is concerned with determining the minimum quantity of data needed for achieving best possible accuracy of identified parameters in transient testing of a lifting rotor blade. Specifically, the problem is that of determining from blade flapping transients caused by blade pitch inputs the equivalent Lock number and the equivalent collective pitch setting. For a given time-dependent blade pitch input function, the running time for the test less than which insufficient parameter accuracy is obtained and more than which little accuracy improvement is achieved was calculated with the aid of the Cramer-Rao lower bound for the parameter covariance matrix.

Banerjee, D.↗

DOE OSTI2019

Multi-scale computational modeling of residual stress in selective laser melting with uncertainty quantification

Selective laser melting (SLM) is a powder-based additive manufacturing technique which creates parts by fusing together successive layers of powder with a laser. The quality of produced parts is highly dependent on the proper selection of processing parameters, requiring significant testing and experimentation to determine parameters for a given machine and material. Computational modeling could potentially be used to shorten this process by identifying parameters through simulation. However, simulating complete SLM builds is challenging due to the difference in scale between the size of the particles and laser used in the build and the size of the part produced. Often, continuum models are employed which approximate the powder as a continuous medium to avoid the need to model powder particles individually. While computationally expedient, continuum models require as inputs effective material properties for the powder which are often difficult to obtain experimentally. Building on previous works which have developed methods for estimating these effective properties along with their uncertainties through the use of detailed models, this work presents a part scale continuum model capable of predicting residual thermal stresses in an SLM build with uncertainty estimates. Model predictions are compared to experimental measurements from the literature.

42 ENGINEERING↗

DOE OSTI2016

Detectable gravitational waves from very strong phase transitions in the general NMSSM

We study the general NMSSM with an emphasis on the parameter regions with a very strong first-order electroweak phase transition (EWPT). In the presence of heavy fields coupled to the Higgs sector, the analysis can be problematic due to the existence of sizable radiative corrections. In this paper we propose a subtraction scheme that helps to circumvent this problem. For simplicity we focus on a parameter region that is by construction hidden from the current collider searches. The analysis proves that (at least) in the identified parameter region the EWPT can be very strong and striking gravitational wave signals can be produced. The corresponding gravitational stochastic background can potentially be detected at the planned space-based gravitational wave observatory eLISA, depending on the specific experiment design that will be approved.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2017

Effects of defects in composite wind turbine blades – Part 1: Characterization and mechanical testing

Abstract. The Montana State University Composite Material Technologies Research Group performed a study to ascertain the effects of defects that often result from the manufacture of composite wind turbine blades. The first step in this multiyear study was to systematically quantify and enter these defects into a database before embedding similar defects into manufactured coupons. Through the Sandia National Laboratories Blade Reliability Collaborative (BRC), it was determined that key defects to investigate were fiber waves and porosity. An inspection of failed commercial-scale wind turbine blades yielded metrics that utilized specific parameters to physically characterize a defect. Methods to easily and consistently discretize, measure, and assess these defects based on the identified parameters were established to allow for statistical analysis. Data relating flaw parameters to frequencies of occurrence were analyzed and found to fit within standard distributions. Additionally, mechanical testing of coupons with flaws based on these physical characterization data was performed to understand effects of these defects. Representative blade materials and manufacturing methods were utilized and both material properties and damage progression were measured. It was observed that flaw parameters directly affected the mechanical response. While the data gathered in this first step are widely useful, it was also intended for use as a foundation for the rest of the study, to perform probabilistic analysis and comparative analysis of progressive damage models.

Nelson, Jared W. (ORCID:0000000207736091)↗

NASA NTRS1999

A Quantitative Study of Oxygen as a Metabolic Regulator

An acute reduction in oxygen (O2) delivery to a tissue is generally associated with a decrease in phosphocreatine, increases in ADP, NADH/NAD, and inorganic phosphate, increased rates of glycolysis and lactate production, and reduced rates of pyruvate and fatty acid oxidation. However, given the complexity of the human bioenergetic system and its components, it is difficult to determine quantitatively how cellular metabolic processes interact to maintain ATP homeostasis during stress (e.g., hypoxia, ischemia, and exercise). Of special interest is the determination of mechanisms relating tissue oxygenation to observed metabolic responses at the tissue, organ, and whole body levels and the quantification of how changes in tissue O2 availability affect the pathways of ATP synthesis and the metabolites that control these pathways. In this study, we extend a previously developed mathematical model of human bioenergetics to provide a physicochemical framework that permits quantitative understanding of O2 as a metabolic regulator. Specifically, the enhancement permits studying the effects of variations in tissue oxygenation and in parameters controlling the rate of cellular respiration on glycolysis, lactate production, and pyruvate oxidation. The whole body is described as a bioenergetic system consisting of metabolically distinct tissue/organ subsystems that exchange materials with the blood. In order to study the dynamic response of each subsystem to stimuli, we solve the ordinary differential equations describing the temporal evolution of metabolite levels, given the initial concentrations. The solver used in the present study is the packaged code LSODE, as implemented in the NASA Lewis kinetics and sensitivity analysis code, LSENS. A major advantage of LSENS is the efficient procedures supporting systematic sensitivity analysis, which provides the basic methods for studying parameter sensitivities (i.e., changes in model behavior due to parameter variation). Sensitivity analysis establishes relationships between model predictions and problem parameters (i.e., initial concentrations, rate coefficients, etc). It helps determine the effects of uncertainties or changes in these input parameters on the predictions, which ultimately are compared with experimental observations in order to validate the model. Sensitivity analysis can identify parameters that must be determined accurately because of their large effect on the model predictions and parameters that need not be known with great precision because they have little or no effect on the solution. This capability may prove to be important in optimizing the design of experiments, thereby reducing the use of animals. This approach can be applied to study the metabolic effects of reduced oxygen delivery to cardiac muscle due to local myocardial ischemia and the effects of acute hypoxia on brain metabolism. Other important applications of sensitivity analysis include identification of quantitatively relevant pathways and biochemical species within an overall mechanism, when examining the effects of a genetic anomaly or pathological state on energetic system components and whole system behavior.

Radhakrishnan, Krishnan↗

NASA NTRS2024

Short–Period Variables in TESS Full–Frame Image Light Curves Identified via Convolutional Neural Networks

The Transiting Exoplanet Survey Satellite (TESS) mission measured light from stars in ∼85% of the sky throughout its 2 yr primary mission, resulting in millions of TESS 30-minute-cadence light curves to analyze in the search for transiting exoplanets. To search this vast data set, we aim to provide an approach that is computationally efficient, produces accurate predictions, and minimizes the required human search effort. We present a convolutional neural network that we train to identify short-period variables. To make a prediction for a given light curve, our network requires no prior target parameters identified using other methods. Our network performs inference on a TESS 30-minute-cadence light curve in ∼5 ms on a single GPU, enabling large-scale archival searches. We present a collection of 14,156 short-period variables identified by our network. The majority of our identified variables fall into two prominent populations, one of close-orbit main-sequence binaries and another of δ Scuti stars. Our neural network model and related code are additionally provided as open-source code for public use and extension.

Convolutional neural networks↗

DOE OSTI2026

Hybrid Cooling and Water Treatment for Resilient, Water-Self-Sufficient Data Centers

The continued growth of data center infrastructure is intensifying demand for freshwater resources, particularly in water-stressed regions, and is increasingly limiting sustainable capacity expansion. This work investigates a conceptual hybrid system that integrates freeze desalination with ultrasonic-assisted ice separation to enable on-site production of pure water from diverse sources, including seawater, brackish groundwater, and reclaimed industrial or agricultural wastewater. Simultaneously, the system produces low-temperature cooling streams that enhance heat removal in high power density computing environments. A process-level thermodynamic analysis is performed across a range of boundary and operating conditions, including variations in feed concentration, freezing temperature, and mass flow rate. The results are presented as performance curves relating feedwater concentration and target purified water output to the corresponding intake flow requirements, enabling estimation of source water demand per unit of Information Technology Equipment (ITE) energy consumption (kWh) across varying data center scales and operational scenarios. The corresponding electrical energy consumption for integrated cooling and water treatment is also evaluated as a function of system operating parameters and target water production levels. These results provide a basis for evaluating system feasibility across different conditions and for identifying parameter ranges in which integrated water treatment and cooling improve resource efficiency, thermal performance, and operational flexibility in data centers.

Elhefny, Aly [ORNL] (ORCID:0000000284907923)↗

DOE OSTI2011

Advanced Instrumentation, Information, and Control System Technologies: Nondestructive Examination Technologies - FY11 Report

Licensees of commercial nuclear power plants in the US are expected to submit license renewal applications for the period of operation of 60 to 80 years which has also been referred to as long term operation (LTO). The greatest challenges to LTO are associated with degradation of passive components as active components are routinely maintained and repaired or placed through maintenance programs. Some passive component degradation concerns include stress corrosion cracking (SCC) of metal components, radiation induced embrittlement of the reactor pressure vessel (RPV), degradation of buried piping, degradation of concrete containment structures, and degradation of cables. Proactive management of passive component aging employs three important elements including online monitoring of degradation, early detection of degradation at precursor stages, and application of prognostics for the prediction of remaining useful life (RUL). This document assesses several nondestructive examination (NDE) measurement technologies for integration into proactive aging management programs. The assessment is performed by discussing the three elements of proactive aging management identified above, considering the current state of the industry with respect to adopting these key elements, and analyzing measurement technologies for monitoring large cracks in metal components, monitoring early degradation at precursor stages, monitoring the degradation of concrete containment structures, and monitoring the degradation of cables. Specific and general needs have been identified through this assessment. General needs identified include the need for environmentally rugged sensors are needed that can operate reliably in an operating reactor environment, the need to identify parameters from precursor monitoring technologies that are unambiguously correlated with the level of pre-macro defect damage, and a methodology for identifying regions where precursor damage is most likely to initiate.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS1989

Preliminary results on noncollocated torque control of space robot actuators

In the Space Station era, more operations will be performed robotically in space in the areas of servicing, assembly, and experiment tending among others. These robots may have various sets of requirements for accuracy, speed, and force generation, but there will be design constraints such as size, mass, and power dissipation limits. For actuation, a leading motor candidate is a dc brushless type, and there are numerous potential drive trains each with its own advantages and disadvantages. This experiment uses a harmonic drive and addresses some inherent limitations, namely its backdriveability and low frequency structural resonances. These effects are controlled and diminished by instrumenting the actuator system with a torque transducer on the output shaft. This noncollocated loop is closed to ensure that the commanded torque is accurately delivered to the manipulator link. The actuator system is modelled and its essential parameters identified. The nonlinear model for simulations will include inertias, gearing, stiction, flexibility, and the effects of output load variations. A linear model is extracted and used for designing the noncollocated torque and position feedback loops. These loops are simulated with the structural frequency encountered in the testbed system. Simulation results are given for various commands in position. The use of torque feedback is demonstrated to yield superior performance in settling time and positioning accuracy. An experimental setup being finished consists of a bench mounted motor and harmonic drive actuator system. A torque transducer and two position encoders, each with sufficient resolution and bandwidth, will provide sensory information. Parameters of the physical system are being identified and matched to analytical predictions. Initial feedback control laws will be incorporated in the bench test equipment and various experiments run to validate the designs. The status of these experiments is given.

Tilley, Scott W.↗

DOE OSTI2022

Proxy-Based Bayesian Inversion Of Poroelastic Simulations To Interpret Strain Tensor Data Measured During Well Testing

The long runtimes of 3D poroelastic numerical simulators makes it impractical to interpret deformation datasets using many inversion schemes. Recent advances in instrumentation have made it possible to measure the strain tensor during well testing, but the lack of robust inversion methods is limiting the ability to interpret these data. We have developed an inversion workflow that reduces the number of computations required to complete a Bayesian inversion using DREAMzs. The workflow trains a KNN model using output from the poroelastic simulator, and then uses the KNN model as a proxy for the simulator during inversion. The workflow also includes a strategy for ensuring the results from the proxy model converge to the results from the simulator, ensuring the accuracy of the final results. An idealized example configured to represent a well test in a deep aquifer is used to verify that the workflow correctly identifies parameters and characterizes noise. Field data measured using strainmeters during an injection test at an oil reservoir in Oklahoma are used to evaluate performance with a real dataset. The workflow identified 265 history matching solutions out of 1240 total simulation runs (21% acceptance ratio), and the results are used to characterize posterior parameter distribution and evaluate the prediction uncertainty. This approach makes it feasible to invert strain data measured during well testing and this has the potential to improve the characterization of aquifers and reservoirs.

Roudini, Soheil↗

NASA NTRS2021

Identifying Planetary Transit Candidates in TESS Full-frame Image Light Curves via Convolutional Neural Networks

The Transiting Exoplanet Survey Satellite(TESS)mission measured light from stars in∼75% of the sky throughout its 2 yr primary mission, resulting in millions of TESS 30-minute-cadence light curves to analyze in the search for transiting exoplanets. To search this vast data trove for transit signals, we aim to provide an approach that both is computationally efficient and produces highly performant predictions. This approach minimizes the required human search effort. We present a convolutional neural network, which we train to identify planetary transit signals and dismiss false positives. To make a prediction for a given light curve, our network requires no prior transit parameters identified using other methods. Our network performs inference on a TESS 30-minute-cadence light curve in∼5 ms on a single GPU, enabling large-scale archival searches. We present 181 new planet candidates identified by our network, which pass subsequent human vetting designed to rule out false positives.Our neural network model is additionally provided as open-source code for public use and extension

Gregory Olmschenk↗

NASA NTRSDate not supplied

Additive Manufacturing and Experimental Characterization of Nickel-Titanium Shape-Memory Alloy Wick Structures and Heat Pipes for Spacecraft Thermal Control

Shape memory alloys (SMA), such as those based on nickel-titanium (NiTi), are increasingly being applied as multifunctional spacecraft components. For thermal management applications, NiTi flow tubing hinges and self-deploying loop heat pipes have been demonstrated. Emerging additive manufacturing (AM) processes are enabling more complex SMA devices than can be formed from conventional plain wire, tubing, and sheet stock materials. This paper presents our progress toward applying powder bed fusion AM to producing porous NiTi wicks and NiTi-H2O heat pipes, which could be embedded in thermally deploying radiators for spacecraft thermal management. AM near-equiatomic NiTi (55.1 wt% Ni) porous wick specimens were produced with a range of deposition parameters. Transient acetone rate-of-rise experiments were performed to estimate wick permeability (K) and average pore radius (r_pore) values and identify parameter sets with high capillary performance. Surface treatments were evaluated to achieve hydrophilic wick structures. Evaluated treatments included chemical oxide growth with H2O2, oxide and sodium titanate growth with NaOH solution, and ultrasonic cleaning with specialty detergents that can remove hydrocarbon contaminants. The most durable hydrophilic surface conditions were obtained with the NaOH treatment. High performing wick deposition parameters were used to produce a full AM NiTi heat pipe, which was treated with NaOH solution to activate the wick. This heat pipe was operated on a test stand in the inverted configuration (upper evaporator and lower condenser), and demonstrated stable nearly isothermal operation for 150 hrs.

Thermal management↗

NASA NTRSDate not supplied

Additive Manufacturing and Experimental Characterization of Nickel-Titanium Shape-Memory Alloy Wick Structures and Heat Pipes for Spacecraft Thermal Control

Thermal management↗

DOE OSTI2012

Data Quality Objectives for WTP Feed Acceptance Criteria - 12043

The Hanford Tank Waste Treatment and Immobilization Plant (WTP) is under construction for the U.S. Department of Energy by Bechtel National, Inc. and subcontractor URS Corporation (contract no. DE-AC27-01RV14136). The plant when completed will be the world's largest nuclear waste treatment facility. Bechtel and URS are tasked with designing, constructing, commissioning, and transitioning the plant to the long term operating contractor to process the legacy wastes that are stored in underground tanks (from nuclear weapons production between the 1940's and the 1980's). Approximately 56 million gallons of radioactive waste is currently stored in these tanks at the Hanford Site in southeastern Washington. There are three major WTP facilities being constructed for processing the tank waste feed. The Pretreatment (PT) facility receives feed where it is separated into a low activity waste (LAW) fraction and a high level waste (HLW) fraction. These fractions are transferred to the appropriate (HLW or LAW) facility, combined with glass former material, and sent to high temperature melters for formation of the glass product. In addition to PT, HLW and LAW, other facilities in WTP include the Laboratory (LAB) for analytical services and the Balance of Facilities (BOF) for plant maintenance, support and utility services. The transfer of staged feed from the waste storage tanks and acceptance in WTP receipt vessels require data for waste acceptance criteria (WAC) parameters from analysis of feed samples. The Data Quality Objectives (DQO) development was a joint team effort between WTP and Tank Operations Contractor (TOC) representatives. The focus of this DQO effort was to review WAC parameters and develop data quality requirements, the results of which will determine whether or not the staged feed can be transferred from the TOC to WTP receipt vessels. The approach involved systematic planning for data collection consistent with EPA guidance for the seven-step DQO process. Data quality requirements for sample collection and analysis of all WAC parameters were specified during the DQO process. There were eighteen key parameters identified with action limits to ensure the feed transfer and receipt would not exceed plant design, safety, permitting, and processing requirements. The remaining WAC parameters were grouped in the category for obtaining data according to WTP contract specifications, regulatory reporting requirements, and for developing the feed campaign processing sequence. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS1976

Maximum likelihood identifier refinements for F-8C adaptive control

Design refinement is described for baseline F-8C adaptive flight test control laws which consist of simplified quadratic-optimal model-following control structures in the pitch and lateral directional axes. The variable gains of both axes are adjusted adaptively by an explicit on-line maximum likelihood parameter identifier. The identifier, consisting of five parallel computing channels which evaluate the likelihood functions at discrete points in parameter space, operates in pitch only, using pitch rate, normal acceleration, and elevator position measurements.

Stein, G.↗

NASA NTRS1982

Rotorcraft Blade Mode Damping Identification from Random Responses Using a Recursive Maximum Likelihood Algorithm

An on line technique is presented for the identification of rotor blade modal damping and frequency from rotorcraft random response test data. The identification technique is based upon a recursive maximum likelihood (RML) algorithm, which is demonstrated to have excellent convergence characteristics in the presence of random measurement noise and random excitation. The RML technique requires virtually no user interaction, provides accurate confidence bands on the parameter estimates, and can be used for continuous monitoring of modal damping during wind tunnel or flight testing. Results are presented from simulation random response data which quantify the identified parameter convergence behavior for various levels of random excitation. The data length required for acceptable parameter accuracy is shown to depend upon the amplitude of random response and the modal damping level. Random response amplitudes of 1.25 degrees to .05 degrees are investigated. The RML technique is applied to hingeless rotor test data. The inplane lag regressing mode is identified at different rotor speeds. The identification from the test data is compared with the simulation results and with other available estimates of frequency and damping.

Molusis, J. A.↗