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DOE OSTI2022

Investigating key cell types and molecules dynamics in PyMT mice model of breast cancer through a mathematical model

The most common kind of cancer among women is breast cancer. Understanding the tumor microenvironment and the interactions between individual cells and cytokines assists us in arriving at more effective treatments. Here, we develop a data-driven mathematical model to investigate the dynamics of key cell types and cytokines involved in breast cancer development. We use time-course gene expression profiles of a mouse model to estimate the relative abundance of cells and cytokines. We then employ a least-squares optimization method to evaluate the model’s parameters based on the mice data. The resulting dynamics of the cells and cytokines obtained from the optimal set of parameters exhibit a decent agreement between the data and predictions. We perform a sensitivity analysis to identify the crucial parameters of the model and then perform a local bifurcation on them. The results reveal a strong connection between adipocytes, IL6, and the cancer population, suggesting them as potential targets for therapies.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1990

Integrated system identification and modal state estimation for control of flexible space structures

A novel approach of integrated system identification and modal state estimation is proposed for control of linear dynamical systems including flexible space structures. There are four steps involved in this approach. First, the relation between a stochastic state space model of a dynamical system and the coefficients of its autoregressive model with exogenous input is derived. Second, an adaptive least-squares transversal predictor is used to estimate the coefficients of the model. Third, a state space model and a steady state Kalman filter gain of the dynamical system are then identified from the coefficients of the model by using the eigensystem realization algorithm. Fourth, a modal state estimator is constructed using the modal parameters of the identified model. On-line implementation of this algorithm can continually improve the modal parameters and the filter gain. It can also gradually update the system model when the system characteristics are slowly changing. A numerical example is used to illustrate the feasibility of the new approach.

Chen, Chung-Wen↗

DOE OSTI2024

Gray-Box Modeling for Distribution Systems With Inverter-Based Resources: Integrating Physics-Based and Data-Driven Approaches

Here, in this paper, we develop a novel gray-box modeling approach for distribution systems with inverter-based resources (IBRs). The proposed gray-box modeling method aims to improve estimation accuracy by taking advantages of both physics-based (white-box) and data-driven (black-box) modeling approaches. To this end, we utilize partial physical knowledge of the system, including the inverters’ structures and control diagrams, as well as the equivalent network model simplified through Kron reduction. The white-box model containing unknown parameters is then constructed with mathematical equations and an optimization-based method is subsequently employed to identify these unknown parameters within the white-box model. Next, the graybox modeling framework is then constructed by embedding the output variables of the white-box model into the input vector of a black-box model (represented using a neural network). Finally, the black-box section is trained using the collected input-output datasets and the gray-box model is then obtained. Furthermore, case studies demonstrate that our gray-box modeling approach effectively improves estimation accuracy compared to purely physics-based or data-driven methods.

42 ENGINEERING↗

NASA NTRS2015

Modeling and Simulation of Vehicle Dynamics on the Surface of Phobos

In this paper we analyze the dynamics of a spacecraft in proximity of Phobos by developing the equations of motion of a test mass in the Phobos rotating frame using a model based on circularly-restricted three body problem, and by analyzing the dynamics of a ATHLETE hopper vehicle interacting with the soil under different soil-interaction conditions. The main conclusion of the numerical studies is that the system response is dominated by the stiffness and damping parameters of the leg springs, with the soil characteristics having a much smaller effect. The system simulations identify ranges of parameters for which the vehicle emerges stably (relying only on the passive viscoelastic damper at each leg) or unstably (needing active attitude control) from the hop. The implication is that further experimental and possibly computational modeling work, as well as site characterization (from precursor missions) will be necessary to obtain validated performance models.

soil-structure interaction↗

NASA NTRSDate not supplied

Simulation of Dynamic Crushing Behavior of Simulated Carbon/Epoxy Stanchions Using MAT58 and MAT213 in LS-DYNA

Carbon fiber-reinforced polymer (CFRP) composites have shown promise as a material for structures designed to absorb energy in crush-style impact loading. In complementing the lightweight and tailorable characteristics of CFRP structures, the benefits of impact energy absorption are particularly interesting in aerospace vehicles that require excellent crashworthiness performance. However, simulating the behavior of CFRP structures in dynamic, crushing-style impact loading is challenging because of the many damage and failure modes that are essential to capture in the model. For the present investigation, CFRP stanchions were tested using a crash sled experimental test rig. The stanchions were designed by the Composite Materials Handbook-17 (CMH-17) Crashworthiness Working Group for the purpose of comparing experimental crash sled tests to corresponding simulations of the tests. The stanchions are C-channel shaped and represent a geometry common in the interior of aerospace vehicle structures. Explicit simulations in LSDYNA were performed using a well-established composite material model (MAT58) and a next-generation material model (MAT213). Fully integrated shell elements were utilized instead of 3D solid elements to limit computation time. In all models, each of the sixteen plies were represented with individual layers of shell elements with tiebreak contact between each adjacent ply pair to simulate interlaminar fracture. Simulating the crushing of the stanchions occurred in two phases. First, the material models were calibrated using flat specimens that were manufactured with the same layup as the stanchions. While the original goal was calibration of material-related properties, meshdependent behavior was observed in simulations with either material model, and an unstructured mesh was selected to remediate undesirable mesh-dependent failure modes. Additionally, for both the MAT58 and MAT213 models, it was found that either the crush force or the failure mode could be modeled accurately, but no set of parameters could be identified to attain both results in the same model. Once satisfactory calibration was achieved, the same material parameters were applied to the stanchion crush simulations. The stanchion simulations showed that MAT213 more accurately predicted the experimentally determined crush force, and both material models predicted key aspects of the experimentally observed failure modes.

Composite Materials↗

DOE OSTI2022

Sensitivity Analysis of an Electrospray Dehumidification System

Electrically enhanced condensation achieved by an electrospray system can enhance dehumidification in HVAC applications if successfully scaled up. The first step towards scale-up is identifying critical design and operating parameters that significantly impact dehumidification for the electrospray system. Sensitivity analysis is one approach for identifying critical parameters. This paper presents a methodology that can efficiently perform quantitative sensitivity analysis on a computationally expensive high fidelity simulation model, which is a computational fluid dynamics (CFD) model of the electrospray system. The methodology employs surrogate modeling and Sobol sensitivity analysis. We estimate the main and total effect Sobol sensitivity indices of four operating parameters of the electrospray system. The results reveal that the most important parameter is the size of the sprayed droplets, followed by the volumetric flow rate of the bulk air and injected water in the system. The water injection velocity of the spray was found to have little to no impact on dehumidification.

Young, David↗

DOE OSTI2024

Characterization of partial wetting by CMAS droplets using multiphase many-body dissipative particle dynamics and data-driven discovery based on PINNs

The molten sand that is a mixture of calcia, magnesia, alumina and silicate, known as CMAS, is characterized by its high viscosity, density and surface tension. The unique properties of CMAS make it a challenging material to deal with in high-temperature applications, requiring innovative solutions and materials to prevent its buildup and damage to critical equipment. Here, we use multiphase many-body dissipative particle dynamics simulations to study the wetting dynamics of highly viscous molten CMAS droplets. The simulations are performed in three dimensions, with varying initial droplet sizes and equilibrium contact angles. We propose a parametric ordinary differential equation (ODE) that captures the spreading radius behaviour of the CMAS droplets. The ODE parameters are then identified based on the physics-informed neural network (PINN) framework. Subsequently, the closed-form dependency of parameter values found by the PINN on the initial radii and contact angles are given using symbolic regression. Finally, we employ Bayesian PINNs (B-PINNs) to assess and quantify the uncertainty associated with the discovered parameters. In brief, this study provides insight into spreading dynamics of CMAS droplets by fusing simple parametric ODE modelling and state-of-the-art machine-learning techniques.

Mechanics↗

NASA NTRS2010

An Extreme-Value Approach to Anomaly Vulnerability Identification

The objective of this paper is to present a method for importance analysis in parametric probabilistic modeling where the result of interest is the identification of potential engineering vulnerabilities associated with postulated anomalies in system behavior. In the context of Accident Precursor Analysis (APA), under which this method has been developed, these vulnerabilities, designated as anomaly vulnerabilities, are conditions that produce high risk in the presence of anomalous system behavior. The method defines a parameter-specific Parameter Vulnerability Importance measure (PVI), which identifies anomaly risk-model parameter values that indicate the potential presence of anomaly vulnerabilities, and allows them to be prioritized for further investigation. This entails analyzing each uncertain risk-model parameter over its credible range of values to determine where it produces the maximum risk. A parameter that produces high system risk for a particular range of values suggests that the system is vulnerable to the modeled anomalous conditions, if indeed the true parameter value lies in that range. Thus, PVI analysis provides a means of identifying and prioritizing anomaly-related engineering issues that at the very least warrant improved understanding to reduce uncertainty, such that true vulnerabilities may be identified and proper corrective actions taken.

Everett, Chris↗

DOE OSTI2014

Identifiability analysis of rotational diffusion tensor and electronic transition moments measured in time-resolved fluorescence depolarization experiment

The subject of this paper is studies of the deterministic identifiability of molecular parameters, such as rotational diffusion tensor components and orientation of electronic transition moments, resulting from the time-resolved fluorescence anisotropy experiment. In the most general case considered, a pair of perpendicularly polarized emissions enables the unique determination of all the rotational diffusion tensor's principal components. The influence of the tensor's symmetry and the associated degeneration of its eigenvalues on the identifiability of the electronic transitions moments is systematically investigated. The analysis reveals that independently of the rotational diffusion tensor's symmetry, the transition moments involved in photoselection and emission processes cannot be uniquely identified without a priori information about their mutual orientation or their orientation with respect to the principal axes of the tensor. Moreover, it is shown that increasing the symmetry of the rotational diffusion tensor deteriorates the degree of the transition moments identifiability. To obtain these results analytically, a novel approach to solve bilinear system of equations for Markov parameters is applied. The effect of the additional information, obtained from fluorescence measurements for different molecular mobilities, to improve the identifiability at various levels of analysis is shown. The effectiveness and reliability of the target analysis method for experimental determination of the molecular parameters is also discussed.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2011

THE SUN'S MERIDIONAL CIRCULATION AND INTERIOR MAGNETIC FIELD

To date, no self-consistent numerical simulation of the solar interior has succeeded in reproducing the observed thinness of the solar tachocline and the persistence of uniform rotation beneath it. Although it is known that the uniform rotation can be explained by the presence of a global-scale confined magnetic field, numerical simulations have thus far failed to produce any solution where such a field remains confined against outward diffusion. We argue that the problem lies in the choice of parameters for which these numerical simulations have been performed. We construct a simple analytical magnetohydrodynamic model of the solar interior and identify several distinct parameter regimes. For realistic solar parameter values, our results are in broad agreement with the tachocline model of Gough and McIntyre. In this regime, meridional flows driven at the base of the convection zone are of sufficient amplitude to hold back the interior magnetic field against diffusion. For the parameter values used in existing numerical simulations, on the other hand, we find that meridional flows are significantly weaker and, we argue, unable to confine the interior field. We propose a method for selecting parameter values in future numerical models.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1988

Learning from examples - Generation and evaluation of decision trees for software resource analysis

A general solution method for the automatic generation of decision (or classification) trees is investigated. The approach is to provide insights through in-depth empirical characterization and evaluation of decision trees for software resource data analysis. The trees identify classes of objects (software modules) that had high development effort. Sixteen software systems ranging from 3,000 to 112,000 source lines were selected for analysis from a NASA production environment. The collection and analysis of 74 attributes (or metrics), for over 4,700 objects, captured information about the development effort, faults, changes, design style, and implementation style. A total of 9,600 decision trees were automatically generated and evaluated. The trees correctly identified 79.3 percent of the software modules that had high development effort or faults, and the trees generated from the best parameter combinations correctly identified 88.4 percent of the modules on the average.

Selby, Richard W.↗

NASA NTRS1990

Microbiological methods for the water recovery systems test, revision 1.1

Current microbiological parameters specified to verify microbiological quality of Space Station Freedom water quality include the enumeration of total bacteria, anaerobes, aerobes, yeasts and molds, enteric bacteria, gram positives, gram negatives, and E. coli. In addition, other parameters have been identified as necessary to support the Water Recovery Test activities to be conducted at the NASA/MSFC later this year. These other parameters include aerotolerant eutrophic mesophiles, legionellae, and an additional method for heterotrophic bacteria. If inter-laboratory data are to be compared to evaluate quality, analytical methods must be eliminated as a variable. Therefore, each participating laboratory must utilize the same analytical methods and procedures. Without this standardization, data can be neither compared nor validated between laboratories. Multiple laboratory participation represents a conservative approach to insure quality and completeness of data. Invariably, sample loss will occur in transport and analyses. Natural variance is a reality on any test of this magnitude and is further enhanced because biological entities, capable of growth and death, are specific parameters of interest. The large variation due to the participation of human test subjects has been noted with previous testing. The resultant data might be dismissed as 'out of control' unless intra-laboratory control is included as part of the method or if participating laboratories are not available for verification. The purpose of this document is to provide standardized laboratory procedures for the enumeration of certain microorganisms in water and wastewater specific to the water recovery systems test. The document consists of ten separate cultural methods and one direct count procedure. It is not intended nor is it implied to be a complete microbiological methods manual.

Rhoads, Tim↗

DOE OSTI2014

Three-dimensional texture analysis of contrast enhanced CT images for treatment response assessment in Hodgkin lymphoma: Comparison with F-18-FDG PET

Purpose: To determine the diagnostic performance of three-dimensional (3D) texture analysis (TA) of contrast-enhanced computed tomography (CE-CT) images for treatment response assessment in patients with Hodgkin lymphoma (HL), compared with F-18-fludeoxyglucose (FDG) positron emission tomography/CT. Methods: 3D TA of 48 lymph nodes in 29 patients was performed on venous-phase CE-CT images before and after chemotherapy. All lymph nodes showed pathologically elevated FDG uptake at baseline. A stepwise logistic regression with forward selection was performed to identify classic CT parameters and texture features (TF) that enable the separation of complete response (CR) and persistent disease. Results: The TF fraction of image in runs, calculated for the 45° direction, was able to correctly identify CR with an accuracy of 75%, a sensitivity of 79.3%, and a specificity of 68.4%. Classical CT features achieved an accuracy of 75%, a sensitivity of 86.2%, and a specificity of 57.9%, whereas the combination of TF and CT imaging achieved an accuracy of 83.3%, a sensitivity of 86.2%, and a specificity of 78.9%. Conclusions: 3D TA of CE-CT images is potentially useful to identify nodal residual disease in HL, with a performance comparable to that of classical CT parameters. Best results are achieved when TA and classical CT features are combined.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2020

Stability boundary and optimal operating parameter identification in milling using Bayesian learning

Here, this paper describes a novel Bayesian learning approach for stability boundary and optimal parameter identification in milling without the knowledge of the underlying tool dynamics or material cutting force coefficients. The paper is divided into two parts. First, a Bayesian learning method for stability lobe identification using test results is described. Each axial depth and spindle speed combination is characterized by a probability of stability which is updated using Bayes’ rule when a test result (stable or unstable) is made available. A novel likelihood function is defined which incorporates knowledge of the stability behavior. Numerical results show convergence to the analytical stability lobe diagram. Second, an adaptive experimental strategy to identify optimal operating parameters that maximize material removal rate is described. Numerical evaluation shows convergence to the optimal operating point with error less than 15 % within ten tests on average. The approach is validated using experimental results. Results show that the proposed method is an efficient and robust learning method to identify the stability lobe diagram and optimal operating parameters with a limited number of tests/data points.

Bayesian machine learning↗

DOE OSTI2016

Towards uniformly dispersed battery electrode composite materials: Characteristics and performance

Battery electrodes are complex mesoscale systems comprised of electroactive components, conductive additives, and binders. In this report, methods for processing electrodes with dispersion of the components are described. To investigate the degree of material dispersion, a spin-coating technique was adopted to provide a thin, uniform layer that enabled observation of the morphology. Distinct differences in the distribution profile of the electrode components arising from individual materials physical affinities were readily identified. Hansen solubility parameter (HSP) analysis revealed pertinent surface interactions associated with materials dispersivity. Further studies demonstrated that HSPs can provide an effective strategy to identify surface modification approaches for improved dispersions of battery electrode materials. Specifically, introduction of surfactantlike functionality such as oleic acid (OA) capping and P3HT-conjugated polymer wrapping on the surface of nanomaterials significantly enhanced material dispersity over the composite electrode. The approach to the surface treatment on the basis of HSP study can facilitate design of composite electrodes with uniformly dispersed morphology and may contribute to enhancing their electrical and electrochemical behaviors. The conductivity of the composites and their electrochemical performance was also characterized. In conclusion, the study illustrates the importance of considering electronic conductivity, electron transfer, and ion transport in the design of environments incorporating active nanomaterials.

25 ENERGY STORAGE↗

DOE OSTI2014

TH-C-18A-09: Exam and Patient Parameters Affecting the DNA Damage Response Following CT Studies

Purpose: To identify exam and patient parameters affecting the biological response to CT studies using in vivo and ex vivo blood samples. Methods: Blood samples were collected under IRB approval from 16 patients undergoing clinically-indicated CT exams. Blood was procured prior to, immediately after and 30minutes following irradiation. A sample of preexam blood was placed on the patient within the exam region for ex vivo analysis. Whole blood samples were fixed immediately following collection and stained for γH2AX to assess DNA damage response (DDR). Median fluorescence of treated samples was compared to non-irradiated control samples for each patient. Patients were characterized by observed biological kinetic response: (a) fast — phosphorylation increased by 2minutes and fell by 30minutes, (b) slow — phosphorylation continued to increase to 30minutes and (c) none — little change was observed or irradiated samples fell below controls. Total dose values were normalized to exam time for an averaged dose-rate in dose/sec for each exam. Relationships between patient biological responses and patient and exam parameters were investigated. Results: A clearer dose response at 30minutes is observed for young patients (<61yoa; R2>0.5) compared to old patients (>61yoa; R{sup 2}<0.11). Fast responding patients were significantly younger than slow responding patients (p<0.05). Unlike in vivo samples, age did not significantly affect the patient response ex vivo. Additionally, fast responding patients received exams with significantly smaller dose-rate than slow responding patients (p<0.05). Conclusion: Age is a significant factor in the biological response suggesting that DDR may be more rapid in a younger population and slower as the population ages. Lack of an agerelated response ex vivo suggests a systemic response to radiation not present when irradiated outside the body. Dose-rate affects the biological response suggesting that patient response may be related to scan timing and dose delivery within an exam protocol. All authors receive(d) funding from a Master Research Agreement from Siemens Healthcare with UCLA Radiological Sciences.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1990

An easily implemented static condensation method for structural sensitivity analysis

A black-box approach to static condensation for sensitivity analysis is presented with illustrative examples of a cube and a car structure. The sensitivity of the structural response with respect to joint stiffness parameter is calculated using the direct method, forward-difference, and central-difference schemes. The efficiency of the various methods for identifying joint stiffness parameters from measured static deflections of these structures is compared. The results indicate that the use of static condensation can reduce computation times significantly and the black-box approach is only slightly less efficient than the standard implementation of static condensation. The ease of implementation of the black-box approach recommends it for use with general-purpose finite element codes that do not have a built-in facility for static condensation.

Gangadharan, S. N.↗

NASA NTRS2015

A New Formulation of the Filter-Error Method for Aerodynamic Parameter Estimation in Turbulence

A new formulation of the filter-error method for estimating aerodynamic parameters in nonlinear aircraft dynamic models during turbulence was developed and demonstrated. The approach uses an estimate of the measurement noise covariance to identify the model parameters, their uncertainties, and the process noise covariance, in a relaxation method analogous to the output-error method. Prior information on the model parameters and uncertainties can be supplied, and a post-estimation correction to the uncertainty was included to account for colored residuals not considered in the theory. No tuning parameters, needing adjustment by the analyst, are used in the estimation. The method was demonstrated in simulation using the NASA Generic Transport Model, then applied to the subscale T-2 jet-engine transport aircraft flight. Modeling results in different levels of turbulence were compared with results from time-domain output error and frequency- domain equation error methods to demonstrate the effectiveness of the approach.

Grauer, Jared A.↗