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At least 1,657 records · Page 92

All sources NASA NTRS DOE OSTI

DOE OSTI2015

ZRBA1, a Mixed EGFR/DNA Targeting Molecule, Potentiates Radiation Response Through Delayed DNA Damage Repair Process in a Triple Negative Breast Cancer Model

Purpose: ZRBA1 is a combi-molecule designed to induce DNA alkylating lesions and to block epidermal growth factor receptor (EGFR) TK domain. Inasmuch as ZRBA1 downregulates the EGFR TK-mediated antisurvival signaling and induces DNA damage, we postulated that it might be a radiosensitizer. The aim of this study was to further investigate the potentiating effect of ZRBA1 in combination with radiation and to elucidate the possible mechanisms of interaction between these 2 treatment modalities. Methods and Materials: The triple negative human breast MDA-MB-468 cancer cell line and mouse mammary cancer 4T1 cell line were used in this study. Clonogenic assay, Western blot analysis, and DNA damage analysis were performed at multiple time points after treatment. To confirm our in vitro findings, in vivo tumor growth delay assay was performed. Results: Our results show that a combination of ZRBA1 and radiation increases the radiation sensitivity of both cell lines significantly with a dose enhancement factor of 1.56, induces significant numbers of DNA strand breaks, prolongs higher DNA damage up to 24 hours after treatment, and significantly increases tumor growth delay in a syngeneic mouse model. Conclusions: Our data suggest that the higher efficacy of this combination could be partially due to increased DNA damage and delayed DNA repair process and to the inhibition of EGFR. The encouraging results of this combination demonstrated a significant improvement in treatment efficiency and therefore could be applicable in early clinical trial settings.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2024

Review of In Situ Sensing for Directed Energy Deposition for Industrial Part Quality Assessment

As the use additive manufacturing (AM) processes continues to grow in critical industries, improved quality assurance methods are becoming increasingly sought after for qualification and certification of AM components. Traditional nondestructive evaluation of printed components is often unable to supply the required confidence in print quality to justify qualification and certification, but the layer-by-layer nature of AM provides unprecedented opportunities for in situ quality inspection. This document summarizes recent developments in process monitoring research specifically related to Directed Energy Deposition (DED). Particular attention is given to three aspects of the highlighted manuscripts: (1) the type of sensors used, (2) features extracted from each sensor modality, and (3) analysis of extracted features for AM quality assessment. Based on the review of the state-of-the-art, several observations have been made. First, none of the reviewed works have applied their trained models to real part geometries, with many of the works relying on single track experiments, thin-walled structures, and cubes. Similarly, there have not been any works demonstrating model generalizability, i.e., a model trained on data from one build allows for fruitful analysis of data from another build. Many works used machine learning techniques to distinguish different process regimes (i.e., normal, keyholing, lack-of-fusion), but very few papers have investigated stochastic variation in an already “optimized” process. Sensor fusion approaches are also limited in the DED sensing literature, but the few works that have employed such techniques have demonstrated the benefits. Finally, registration of in situ data to the build coordinate system is of paramount importance to producing industrially relevant in situ monitoring systems. Data registration allows direct correlations between process anomalies detected in the process monitoring data to localized departures in part quality, but such techniques are generally lacking in the current literature.

36 MATERIALS SCIENCE↗

NASA NTRS1983

Blade loss transient dynamics analysis with flexible bladed disk

The transient dynamic response of a flexible bladed disk on a flexible rotor in a two rotor system is formulated by modal synthesis and a Lagrangian approach. Only the nonequilibrated one diameter flexible mode is considered for the flexible bladed disk, while the two flexible rotors are represented by their normal modes. The flexible bladed disk motion is modeled as a combination of two one diameter standing waves, and is coupled inertially and gyroscopically to the flexible rotors. Application to a two rotor model shows that a flexible bladed disk on one rotor can be driven into resonance by an unbalance in the other rotor, and at a frequency equal to the difference in the rotor speeds.

Gallardo, V. C.↗

NASA NTRS1984

A degree of controllability definition - Fundamental concepts and application to modal systems

Starting from basic physical considerations, this paper develops a concept of the degree of controllability of a control system, and then develops numerical methods to generate approximate values of the degree of controllability for any linear time-invariant system. In many problems, such as the control of future, very large, flexible spacecraft and certain chemical process control problems, the question of how to choose the number and locations of the control system actuators is an important one. The results obtained here offer the control system designer a tool which allows him to rank the effectiveness of alternative actuator distributions, and hence to choose the actuator locations on a rational basis. The degree of controllability is shown to take a particularly simple form when the dynamic equations of a satellite are in second-order modal form. The degree of controllability concept has still other fundamental uses - it allows one to study the system structural relations between the various inputs and outputs of a linear system, which has applications to decoupling and model reduction.

Viswanathan, C. N.↗

NASA NTRS1991

HITCAN for actively cooled hot-composite thermostructural analysis

A computer code, high temperature composite analyzer (HITCAN), was developed to analyze/design hot metal matrix composite structures. HITCAN is a general purpose code for predicting the global structural and local stress-strain response of multilayered (arbitrarily oriented) metal matrix structures both at the constituent (fiber, matrix, and interphase) and the structural level, including the fabrication process effects. The thermomechanical properties of the constituents are considered to be nonlinearly dependent on several parameters, including temperature, stress, and stress rate. The computational procedure employs an incremental iterative nonlinear approach utilizing a multifactor-interaction material behavior model, i.e., the material properties are expressed in terms of a product of several factors that affect the properties. HITCAN structural analysis capabilities (static, load stepping - a multistep static analysis with material properties updated at each step, modal, and buckling) for cooled hot structures are demonstrated through a specific example problem.

Chamis, C. C.↗

NASA NTRS1992

HITCAN for actively cooled hot-composite thermostructural analysis

Chamis, C. C.↗

NASA NTRS2016

Extracting Damping Ratio from Dynamic Data and Numerical Solutions

There are many ways to extract damping parameters from data or models. This Technical Memorandum provides a quick reference for some of the more common approaches used in dynamics analysis. Described are six methods of extracting damping from data: the half-power method, logarithmic decrement (decay rate) method, an autocorrelation/power spectral density fitting method, a frequency response fitting method, a random decrement fitting method, and a newly developed half-quadratic gain method. Additionally, state-space models and finite element method modeling tools, such as COMSOL Multiphysics (COMSOL), provide a theoretical damping via complex frequency. Each method has its advantages which are briefly noted. There are also likely many other advanced techniques in extracting damping within the operational modal analysis discipline, where an input excitation is unknown; however, these approaches discussed here are objective, direct, and can be implemented in a consistent manner.

Casiano, M. J.↗

NASA NTRS2019

Fusion of Visible and Thermal-Infrared Imagery for SLAM for Landing on Icy Moons

This paper addresses the problem of localization for landing on the surface of icy moons, like Europa or Enceladus. Due to the possibility of specular reflection as well as high bulk albedo, icy surfaces present new challenges that make traditional vision-based navigation systems relying on visible imagery unreliable. We propose augmenting visible light cameras with a thermal-infrared camera using inverse-depth parameterized monocular EKF-SLAM to address problems arising from the appearance of icy moons. Results were obtained from a novel procedural Europa surface simulation which models the appearance and the thermal properties simultaneously from physically-based methods. In this framework, we show that thermal features improve localization by 23% on average when compared to a visible camera. Moreover, fusing both sensing modalities increases the improvement in localization to 31% on average, compared to using a visible light camera alone.

thermal vision↗

NASA NTRSDate not supplied

Analyzing Natural Language Context in Human-Machine Teaming using Supervised Machine Learning

Building a foundation for trustworthiness and trust verification in multi-asset teaming is the research challenge of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR). The Design Reference Mission (DRM) for ATTRACTOR is a search and rescue mission objective governed by a multi-member team consisting of human and machine operators. A crucial component to the effort is the communication between humans and autonomous agents throughout both planning and execution stages of the mission. Intuitive communication methods and modalities are posited as critical enablers for certifying trust and trustworthiness. This paper reports on the data collection and analysis conducted in support of the Human Informed Natural-language GANs Evaluation (HINGE)project to attain explainable and trusted communication between human-machine assets. Two identically curated image description datasets were acquired for HINGE, both consisting of two unique input modalities (typed vs. verbal) and retrieved in two distinct contexts (general vs. specific). The gathered datasets were assessed and compared using Parts-of-Speech (POS)features, sentence similarity metrics, and linguistic analysis. Then, the datasets were modeled and tested separately and in combination with one another using machine learning algorithms. The comparison and testing results reveal a superior dataset, by which a preferred context and input is understood, for generating image representations of missing persons using a Generative Adversarial Network (GAN).

Bryan A Barrows↗

NASA NTRS1975

Results of NASTRAN modal analyses and ground vibration tests on the YF-12A airplane

The YF-12A aircraft, a delta-winged vehicle powered by two jet engines, was utilized in an investigation of the structural dynamic characteristics of a large, flexible, supersonic research vehicle. A large NASA structural analysis (NASTRAN) finite-element model was used to compute the ten lowest frequency symmetric and ten lowest frequency antisymmetric modes for the YF-12A aircraft. The results of the analysis were compared with experimental data obtained in a ground vibration test conducted with the completed aircraft. It was found that the finite-element structural model employed provides an adequate prediction of the dynamic behavior of the aircraft structure in the case of basic wing and body modes.

Kordes, E. E.↗

NASA NTRS1981

Effects of truncation in modal representations of thermal convection

The Galerkin equations for convection in a sphere are examined to determine which physical processes are neglected by the severe truncation of the equations of motion. It is demonstrated that the gross features of the flow are affected by truncation in the horizontal direction, with all of the models considered being well resolved in the vertical direction. One of the effects of truncation is to enhance the high-wave number end of the kinetic energy and thermal variance spectra. The examples cited indicate that as long as the kinetic energy spectrum decreases with wave number, a truncation gives a qualitatively correct solution. Conclusions are tested by calculating solutions to the equations of motion for several values of the Rayleigh number and the limit of horizontal spatial resolution.

Marcus, P. S.↗

DOE OSTI2015

TU-AB-201-11: A Novel Theoretical Framework for MRI-Only Image Guided LDR Prostate and Breast Brachytherapy Implant Dosimetry

Purpose: To propose a novel framework for accurate model-based dose calculations using only MR images for LDR prostate and breast seed implant brachytherapy. Methods: Model-based dose calculation methodologies recommended by TG-186 require further knowledge about specific tissue composition, which is challenging with MRI. However, relying on MRI-only for implant dosimetry would reduce the soft tissue delineation uncertainty, costs, and uncertainties associated with multi-modality registration and fusion processes. We propose a novel framework to address this problem using quantitative MRI acquisitions and reconstruction techniques. The framework includes three steps: (1) Identify the locations of seeds(2) Identify the presence (or absence) of calcification(s)(3) Quantify the water and fat content in the underlying tissueSteps (1) and (2) consider the sources that limit patient dosimetry, particularly the inter-seed attenuation and the calcified regions; while step (3) targets the quantification of the tissue composition to consider the heterogeneities in the medium. Our preliminary work has shown that the seeds and the calcifications can be identified with MRI using both the magnitude and the phase images. By employing susceptibility-weighted imaging with specific post-processing techniques, the phase images can be further explored to distinguish the seeds from the calcifications. Absolute quantification of tissue, water, and fat content is feasible and was previously demonstrated in phantoms and in-vivo applications, particularly for brain diseases. The approach relies on the proportionality of the MR signal to the number of protons in an image volume. By employing appropriate correction algorithms for T1 - and T2*-related biases, B1 transmit and receive field inhomogeneities, absolute water/fat content can be determined. Results: By considering calcification and interseed attenuation, and through the knowledge of water and fat mass density, accurate patient-specific implant dosimetry can be achieved with MRI-only. Conclusion: The proposed framework showed that model-based dose calculation is feasible using MRI-only state-of-the-art techniques.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2017

Modal analysis of dislocation vibration and reaction attempt frequency

Transition state theory is a fundamental approach for temporal coarse-graining. It estimates the reaction rate for a transition processes by quantifying the activation free energy and attempt frequency for the unit process. To calculate the transition rate of a gliding dislocation, the attempt frequency is often obtained from line tension estimates of dislocation vibrations, a highly simplified model of dislocation behavior. This work revisits the calculation of attempt frequency for a dislocation bypassing an obstacle, in this case a self-interstitial atom (SIA) loop. First, a direct calculation of the vibrational characteristics of a finite pinned dislocation segment is compared to line tension estimates before moving to the more complex case of dislocation-obstacle bypass. The entropic factor associated with the attempt frequency is calculated for a finite dislocation segment and for an infinite glide dislocation interacting with an SIA loop. Lastly, it is found to be dislocation length independent for three cases of dislocation-self interstitial atom (SIA) loop interactions.

36 MATERIALS SCIENCE↗

DOE OSTI2014

Relaxation dynamics in quantum dissipative systems: The microscopic effect of intramolecular vibrational energy redistribution

We investigate the effect of inter-mode coupling on the vibrational relaxation dynamics of molecules in weak dissipative environments. The simulations are performed within the reduced density matrix formalism in the Markovian regime, assuming a Lindblad form for the system-bath interaction. The prototypical two-dimensional model system representing two CO molecules approaching a Cu(100) surface is adapted from an ab initio potential, while the diatom-diatom vibrational coupling strength is systematically varied. In the weak system-bath coupling limit and at low temperatures, only first order non-adiabatic uni-modal coupling terms contribute to surface-mediated vibrational relaxation. Since dissipative dynamics is non-unitary, the choice of representation will affect the evolution of the reduced density matrix. Two alternative representations for computing the relaxation rates and the associated operators are thus compared: the fully coupled spectral basis, and a factorizable ansatz. The former is well-established and serves as a benchmark for the solution of Liouville-von Neumann equation. In the latter, a contracted grid basis of potential-optimized discrete variable representation is tailored to incorporate most of the inter-mode coupling, while the Lindblad operators are represented as tensor products of one-dimensional operators, for consistency. This procedure results in a marked reduction of the grid size and in a much more advantageous scaling of the computational cost with respect to the increase of the dimensionality of the system. The factorizable method is found to provide an accurate description of the dissipative quantum dynamics of the model system, specifically of the time evolution of the state populations and of the probability density distribution of the molecular wave packet. The influence of intra-molecular vibrational energy redistribution appears to be properly taken into account by the new model on the whole range of coupling strengths. It demontrates that most of the mode mixing during relaxation is due to the potential part of the Hamiltonian and not to the coupling among relaxation operators.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

COVID-19 Joint Pandemic Modeling and Analysis Platform

The non-pharmaceutical intervention to reduce the impact and spread of COVID-19 requires the development of policies and guidance through a collaborative effort among government, academia, medicine, and citizens. To operationalize this effort, we have developed an all-encompassing situational awareness platform that can process multi-modal and multi-source data allowing informed decision making. Besides, showing the current spread of infection, the platform also captures the impact of human dynamics on the infection spread, location, and availability of critical infrastructure, prediction, and high-performance computing driven simulation. The platform is extensible, allowing third-party integration and services to consume the curated data and analytics in near real-time. We believe the platform will augment critical decision making for reducing the impact and spread of the pandemic.

Thakur, Gautam↗

DOE OSTI2026

Optimizing Transportation Networks for E-Waste Reverse Logistics: A Multi-Modal Cost Allocation and Pricing Strategy

The exponential growth of electronic waste (e-waste) poses critical challenges for sustainable reverse logistics and transportation network optimization. This study develops a dual-channel transportation framework for e-waste logistics that integrates dynamic freight pricing, cost allocation mechanisms, and game-theoretic coordination. The model captures interactions between centralized hubs and distributed processing networks, accounting for freight rate elasticity, volume allocation, and capacity constraints. Using Stackelberg game theory and cost-sharing strategies, the framework optimizes transportation efficiency and profit distribution across logistics channels. Numerical simulations show that the dual-channel structure increases centralized hub profit by 226.8% compared to baseline single-channel operations, while boosting total transported volume by 1.2% and nearly doubling freight collector profit under cost-sharing. Scenario analyses across regional infrastructures reveal that network density, policy incentives, and logistics costs shape routing efficiency and profit allocation. These findings suggest that coordinated strategies combining dynamic pricing, targeted infrastructure investment, and strategic cost allocation are needed to design efficient, resilient, and regionally adaptable e-waste transportation systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2016

Establishing Cost-Effective Allocation of Proton Therapy for Breast Irradiation

Purpose: Cardiac toxicity due to conventional breast radiation therapy (RT) has been extensively reported, and it affects both the life expectancy and quality of life of affected women. Given the favorable oncologic outcomes in most women irradiated for breast cancer, it is increasingly paramount to minimize treatment side effects and improve survivorship for these patients. Proton RT offers promise in limiting heart dose, but the modality is costly and access is limited. Using cost-effectiveness analysis, we provide a decision-making tool to help determine which breast cancer patients may benefit from proton RT referral. Methods and Materials: A Markov cohort model was constructed to compare the cost-effectiveness of proton versus photon RT for breast cancer management. The model was analyzed for different strata of women based on age (40 years, 50 years, and 60 years) and the presence or lack of cardiac risk factors (CRFs). Model entrants could have 1 of 3 health states: healthy, alive with coronary heart disease (CHD), or dead. Base-case analysis assumed CHD was managed medically. No difference in tumor control was assumed between arms. Probabilistic sensitivity analysis was performed to test model robustness and the influence of including catheterization as a downstream possibility within the health state of CHD. Results: Proton RT was not cost-effective in women without CRFs or a mean heart dose (MHD) <5 Gy. Base-case analysis noted cost-effectiveness for proton RT in women with ≥1 CRF at an approximate minimum MHD of 6 Gy with a willingness-to-pay threshold of $100,000/quality-adjusted life-year. For women with ≥1 CRF, probabilistic sensitivity analysis noted the preference of proton RT for an MHD ≥5 Gy with a similar willingness-to-pay threshold. Conclusions: Despite the cost of treatment, scenarios do exist whereby proton therapy is cost-effective. Referral for proton therapy may be cost-effective for patients with ≥1 CRF in cases for which photon plans are unable to achieve an MHD <5 Gy.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2025

Multi-modality deep learning for pulse prediction in homogeneous nonlinear systems via parametric conversion

In this Letter, we introduce FusionNet, a multi-modality deep learning framework designed to predict and analyze output pulses in high-power rare-earth-doped laser systems driving parametric conversion in homogeneous guided nonlinear media. FusionNet integrates temporal, spectral, and physical experimental conditions to model ultrafast nonlinear phenomena, including parametric nonlinear frequency conversion, self-phase modulation, and cross-phase modulation in homogeneous guided systems such as gas-filled hollow-core fibers. These systems bridge physical models with experimental data, advancing our understanding of light-guiding principles and nonlinear interactions while expediting the design and optimization of on-demand high-power, high-brightness systems. Our results demonstrate a 73% reduction in prediction error and an 83% improvement in computational efficiency compared to conventional neural networks. This work establishes a new paradigm for accelerating parametric simulations and optimizing experimental designs in high-power laser systems, with further implications for high-precision spectroscopy, quantum information science, and distributed entangled interconnects.

47 OTHER INSTRUMENTATION↗