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NASA NTRS1975

Methods for Combining Payload Parameter Variations with Input Environment

Methods are presented for calculating design limit loads compatible with probabilistic structural design criteria. The approach is based on the concept that the desired limit load, defined as the largest load occuring in a mission, is a random variable having a specific probability distribution which may be determined from extreme-value theory. The design limit load, defined as a particular value of this random limit load, is the value conventionally used in structural design. Methods are presented for determining the limit load probability distributions from both time-domain and frequency-domain dynamic load simulations. Numerical demonstrations of the methods are also presented.

Merchant, D. H.↗

NASA NTRS1976

Methods for combining payload parameter variations with input environment

Methods are presented for calculating design limit loads compatible with probabilistic structural design criteria. The approach is based on the concept that the desired limit load, defined as the largest load occurring in a mission, is a random variable having a specific probability distribution which may be determined from extreme-value theory. The design limit load, defined as a particular of this random limit load, is the value conventionally used in structural design. Methods are presented for determining the limit load probability distributions from both time-domain and frequency-domain dynamic load simulations. Numerical demonstrations of the method are also presented.

Merchant, D. H.↗

DOE OSTI2026

Monte Carlo Event Generation with Continuous Normalizing Flows

We apply continuous normalizing flows trained with the flow matching method to the problem of phase-space sampling in Monte Carlo event generation for high-energy collider physics. Focusing on lepton-pair and top-quark pair production with multiple jets, the two computationally most expensive processes at the Large Hadron Collider, we train helicity-conditioned continuous normalizing flows to remap the random numbers used in matrix element evaluation. Compared to standard methods, we achieve unweighting efficiency improvements by factors of up to 184 and 25 for the two processes at their respective highest jet number, at the cost of an increased evaluation time. When combining the advantages of continuous normalizing flows with the fast evaluation times of coupling-layer-based flows, using the RegFlow approach, we find parton-level unweighted event generation walltime gains of about a factor of 10 at the highest jet numbers. These substantial gains highlight the promise of samplers based on machine learning for next-generation collider experiments.

Bothmann, Enrico [CERN; Gottingen U.] (ORCID:00000↗

DOE OSTI2012

External Pelvic and Vaginal Irradiation Versus Vaginal Irradiation Alone as Postoperative Therapy in Medium-Risk Endometrial Carcinoma-A Prospective Randomized Study

Purpose: To evaluate the value of adjuvant external beam pelvic radiotherapy as adjunct to vaginal brachytherapy (VBT) in medium-risk endometrial carcinoma, with regard to locoregional tumor control, recurrences, survival, and toxicity. Methods and Materials: Consecutive series of 527 evaluable patients were included in this randomized trial. Median follow-up for patients alive was 62 months. The primary study endpoints were locoregional recurrences and overall survival. Secondary endpoints were recurrence-free survival, recurrence-free interval, cancer-specific survival, and toxicity. Results: Five-year locoregional relapse rates were 1.5% after external beam radiotherapy (EBRT) plus VBT and 5% after vaginal irradiation alone (p = 0.013), and 5-year overall survival rates were 89% and 90%, respectively (p = 0.548). Endometrial cancer-related death rates were 3.8% after EBRT plus VBT and 6.8% after VBT (p = 0.118). Pelvic recurrences (exclusively vaginal recurrence) were reduced by 93% by the addition of EBRT to VBT. Deep myometrial infiltration was a significant prognostic factor in this medium-risk group of endometrioid carcinomas but not International Federation of Gynecology and Obstetrics grade or DNA ploidy. Combined radiotherapy was well tolerated, with serious (Grade 3) late side effects of less than 2%. However, there was a significant difference in favor of VBT alone. Conclusions: Despite a significant locoregional control benefit with combined radiotherapy, no survival improvement was recorded, but increased late toxicity was noted in the intestine, bladder, and vagina. Combined RT should probably be reserved for high-risk cases with two or more high-risk factors. VBT alone should be the adjuvant treatment option for purely medium-risk cases.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2015

Dosimetry Modeling for Focal Low-Dose-Rate Prostate Brachytherapy

Purpose: Focal brachytherapy targeted to an individual lesion(s) within the prostate may reduce side effects experienced with whole-gland brachytherapy. The outcomes of a consensus meeting on focal prostate brachytherapy were used to investigate optimal dosimetry of focal low-dose-rate (LDR) prostate brachytherapy targeted using multiparametric magnetic resonance imaging (mp-MRI) and transperineal template prostate mapping (TPM) biopsy, including the effects of random and systematic seed displacements and interseed attenuation (ISA). Methods and Materials: Nine patients were selected according to clinical characteristics and concordance of TPM and mp-MRI. Retrospectively, 3 treatment plans were analyzed for each case: whole-gland (WG), hemi-gland (hemi), and ultra-focal (UF) plans, with 145-Gy prescription dose and identical dose constraints for each plan. Plan robustness to seed displacement and ISA were assessed using Monte Carlo simulations. Results: WG plans used a mean 28 needles and 81 seeds, hemi plans used 17 needles and 56 seeds, and UF plans used 12 needles and 25 seeds. Mean D90 (minimum dose received by 90% of the target) and V100 (percentage of the target that receives 100% dose) values were 181.3 Gy and 99.8% for the prostate in WG plans, 195.7 Gy and 97.8% for the hemi-prostate in hemi plans, and 218.3 Gy and 99.8% for the focal target in UF plans. Mean urethra D10 was 205.9 Gy, 191.4 Gy, and 92.4 Gy in WG, hemi, and UF plans, respectively. Mean rectum D2 cm{sup 3} was 107.5 Gy, 77.0 Gy, and 42.7 Gy in WG, hemi, and UF plans, respectively. Focal plans were more sensitive to seed displacement errors: random shifts with a standard deviation of 4 mm reduced mean target D90 by 14.0%, 20.5%, and 32.0% for WG, hemi, and UF plans, respectively. ISA has a similar impact on dose-volume histogram parameters for all plan types. Conclusions: Treatment planning for focal LDR brachytherapy is feasible. Dose constraints are easily met with a notable reduction to organs at risk. Treating smaller targets makes seed positioning more critical.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS2011

Coherent Backscattering by Polydisperse Discrete Random Media: Exact T-Matrix Results

The numerically exact superposition T-matrix method is used to compute, for the first time to our knowledge, electromagnetic scattering by finite spherical volumes composed of polydisperse mixtures of spherical particles with different size parameters or different refractive indices. The backscattering patterns calculated in the far-field zone of the polydisperse multiparticle volumes reveal unequivocally the classical manifestations of the effect of weak localization of electromagnetic waves in discrete random media, thereby corroborating the universal interference nature of coherent backscattering. The polarization opposition effect is shown to be the least robust manifestation of weak localization fading away with increasing particle size parameter.

Mishchenko, Michael I.↗

DOE OSTI2012

'Pharyngocise': Randomized Controlled Trial of Preventative Exercises to Maintain Muscle Structure and Swallowing Function During Head-and-Neck Chemoradiotherapy

Purpose: Dysphagia after chemoradiotherapy is common. The present randomized clinical trial studied the effectiveness of preventative behavioral intervention for dysphagia compared with the 'usual care.' Methods and Materials: A total of 58 head-and-neck cancer patients treated with chemoradiotherapy were randomly assigned to usual care, sham swallowing intervention, or active swallowing exercises (pharyngocise). The intervention arms were treated daily during chemoradiotherapy. The primary outcome measure was muscle size and composition (determined by T{sub 2}-weighted magnetic resonance imaging). The secondary outcomes included functional swallowing ability, dietary intake, chemosensory function, salivation, nutritional status, and the occurrence of dysphagia-related complications. Results: The swallowing musculature (genioglossus, hyoglossuss, and mylohyoid) demonstrated less structural deterioration in the active treatment arm. The functional swallowing, mouth opening, chemosensory acuity, and salivation rate deteriorated less in the pharyngocise group. Conclusion: Patients completing a program of swallowing exercises during cancer treatment demonstrated superior muscle maintenance and functional swallowing ability.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2022

MAPredict: Static Analysis Driven Memory Access Prediction Framework for Modern CPUs

Application memory access patterns are crucial in deciding how much traffic is served by the cache and forwarded to the dynamic random-access memory (DRAM). However, predicting such memory traffic is difficult because of the interplay of prefetchers, compilers, parallel execution, and innovations in manufacturer-specific micro-architectures. This research introduced MAPredict, a static analysis-driven framework that addresses these challenges to predict last-level cache (LLC)-DRAM traffic. By exploring and analyzing the behavior of modern Intel processors, MAPredict formulates cache-aware analytical models. MAPredict invokes these models to predict LLC-DRAM traffic by combining the application model, machine model, and user-provided hints to capture dynamic information. MAPredict successfully predicts LLC-DRAM traffic for different regular access patterns and provides the means to combine static and empirical observations for irregular access patterns. Evaluating 130 workloads from six applications on recent Intel micro-architectures, MAPredict yielded an average accuracy of 99% for streaming, 91% for strided, and 92% for stencil patterns. By coupling static and empirical methods, up to 97% average accuracy was obtained for random access patterns on different micro-architectures.

Monil, M. A. H.↗

NASA NTRS1990

Stationary and nonstationary random vibrations of laminated composite plates via a higher order theory

Higher order shear deformation theory is utilized to study he weakly stationary and nonstationary random vibrations of cross-ply laminated plates. Normal mode method, in conjunction with the biorthogonality condition, for the nonsymmetric differential equations is applied. Detailed derivation is given for the governing equations, biorthogonality condition, the generalized mass and the generalized forces. Results are listed for a plate which is simply supported at all the edges, and subjected to a point load which is either timewise stationary or nonstationary random process.

Elishakoff, Isaac↗

DOE OSTI2020

Hole–hole Tamm–Dancoff-approximated density functional theory: A highly efficient electronic structure method incorporating dynamic and static correlation

The study of photochemical reaction dynamics requires accurate as well as computationally efficient electronic structure methods for the ground and excited states. While time-dependent density functional theory (TDDFT) is not able to capture static correlation, complete active space self-consistent field methods neglect much of the dynamic correlation. Hence, inexpensive methods that encompass both static and dynamic electron correlation effects are of high interest. Here, we revisit hole–hole Tamm–Dancoff approximated (hh-TDA) density functional theory for this purpose. The hh-TDA method is the hole–hole counterpart to the more established particle–particle TDA (pp-TDA) method, both of which are derived from the particle–particle random phase approximation (pp-RPA). In hh-TDA, the N-electron electronic states are obtained through double annihilations starting from a doubly anionic (N+2 electron) reference state. In this way, hh-TDA treats ground and excited states on equal footing, thus allowing for conical intersections to be correctly described. Furthermore, the treatment of dynamic correlation is introduced through the use of commonly employed density functional approximations to the exchange-correlation potential. Additionally, we show that hh-TDA is a promising candidate to efficiently treat the photochemistry of organic and biochemical systems that involve several low-lying excited states—particularly those with both low-lying ππ* and nπ* states where inclusion of dynamic correlation is essential to describe the relative energetics. In contrast to the existing literature on pp-TDA and pp-RPA, we employ a functional-dependent choice for the response kernel in pp- and hh-TDA, which closely resembles the response kernels occurring in linear response and collinear spin-flip TDDFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Privacy Amplification for Episodic Training Methods

It has been shown that differential privacy bounds improve when subsampling within a randomized mechanism. Episodic training, utilized in many standard machine learning techniques, uses a multistage subsampling procedure which has not been previously analyzed for privacy bound amplification. In this paper, we focus on improving the calculation of privacy bounds in episodic training by thoroughly analyzing privacy amplification due to subsampling with a multi-stage subsampling procedure. The newly developed bound can be incorporated into existing privacy accounting methods.

Tombs, Vandy↗

DOE OSTI2024

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗

DOE OSTI2024

Linac_Gen: integrating machine learning and particle-in-cell methods for enhanced beam dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in linacs over traditional methods through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of linac systems, as evidenced in its application to Fermilab's PIP-II linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗

DOE OSTI2018

Studying language evolution in the age of big data

The increasing availability of large digital corpora of cross-linguistic data is revolutionizing many branches of linguistics. Overall, it has triggered a shift of attention from detailed questions about individual features to more global patterns amenable to rigorous, but statistical, analyses. This engenders an approach based on successive approximations where models with simplified assumptions result in frameworks that can then be systematically refined, always keeping explicit the methodological commitments and the assumed prior knowledge. Therefore, they can resolve disputes between competing frameworks quantitatively by separating the support provided by the data from the underlying assumptions. These methods, though, often appear as a ‘black box’ to traditional practitioners. In fact, the switch to a statistical view complicates comparison of the results from these newer methods with traditional understanding, sometimes leading to misinterpretation and overly broad claims. We describe here this evolving methodological shift, attributed to the advent of big, but often incomplete and poorly curated, data, emphasizing the underlying similarity of the newer quantitative to the traditional comparative methods and discussing when and to what extent the former have advantages over the latter. In this review, we cover briefly both randomization tests for detecting patterns in a largely model-independent fashion and phylolinguistic methods for a more model-based analysis of these patterns. We foresee a fruitful division of labor between the ability to computationally process large volumes of data and the trained linguistic insight declaring worthy prior commitments and interesting hypotheses in need of comparison.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

NASA NTRS1975

On the prediction of critical flutter conditions from subcritical response data and some related wind-tunnel experience

Methods of interpreting response measurements which could be amenable to flight flutter testing procedures were studied analytically and in the wind tunnel. One suggested scheme, which requires evaluation, is an iterative technique in which derivatives obtained from subcritical response data are used to indicate the approach to flutter. A simplification of this procedure was considered by examining the manner in which a single characteristic of the subcritical response behaves in relation to variations of the density or dynamic pressure in the approach to flutter. The use of this single parameter scheme was examined for random excitation as well as for sinusoidal forcing. The feasibility of the method is illustrated by several examples and the relative merits of random and sinusoidal excitation are discussed.

Houbolt, J. C.↗

DOE OSTI2023

Comparing Individualized Survival Predictions From Random Survival Forests and Multistate Models in the Presence of Missing Data: A Case Study of Patients With Oropharyngeal Cancer

Background: In recent years, interest in prognostic calculators for predicting patient health outcomes has grown with the popularity of personalized medicine. These calculators, which can inform treatment decisions, employ many different methods, each of which has advantages and disadvantages. Methods: We present a comparison of a multistate model (MSM) and a random survival forest (RSF) through a case study of prognostic predictions for patients with oropharyngeal squamous cell carcinoma. The MSM is highly structured and takes into account some aspects of the clinical context and knowledge about oropharyngeal cancer, while the RSF can be thought of as a black-box non-parametric approach. Key in this comparison are the high rate of missing values within these data and the different approaches used by the MSM and RSF to handle missingness. Results: We compare the accuracy (discrimination and calibration) of survival probabilities predicted by both approaches and use simulation studies to better understand how predictive accuracy is influenced by the approach to (1) handling missing data and (2) modeling structural/disease progression information present in the data. We conclude that both approaches have similar predictive accuracy, with a slight advantage going to the MSM. Conclusions: Although the MSM shows slightly better predictive ability than the RSF, consideration of other differences are key when selecting the best approach for addressing a specific research question. These key differences include the methods’ ability to incorporate domain knowledge, and their ability to handle missing data as well as their interpretability, and ease of implementation. Ultimately, selecting the statistical method that has the most potential to aid in clinical decisions requires thoughtful consideration of the specific goals.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

A multilevel stochastic collocation method for SPDEs

We present a multilevel stochastic collocation method that, as do multilevel Monte Carlo methods, uses a hierarchy of spatial approximations to reduce the overall computational complexity when solving partial differential equations with random inputs. For approximation in parameter space, a hierarchy of multi-dimensional interpolants of increasing fidelity are used. Rigorous convergence and computational cost estimates for the new multilevel stochastic collocation method are derived and used to demonstrate its advantages compared to standard single-level stochastic collocation approximations as well as multilevel Monte Carlo methods.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2011

Latest developments in seismic texture analysis for subsurface structure, facies, and reservoir characterization: A review

In exploration geology and geophysics, seismic texture is still a developing concept that has not been sufficiently known, although quite a number of different algorithms have been published in the literature. This paper provides a review of the seismic texture concepts and methodologies, focusing on latest developments in seismic amplitude texture analysis, with particular reference to the gray level co-occurrence matrix (GLCM) and the texture model regression (TMR) methods. The GLCM method evaluates spatial arrangements of amplitude samples within an analysis window using a matrix (a two-dimensional histogram) of amplitude co-occurrence. The matrix is then transformed into a suite of texture attributes, such as homogeneity, contrast, and randomness, which provide the basis for seismic facies classification. The TMR method uses a texture model as reference to discriminate among seismic features based on a linear, least-squares regression analysis between the model and the data within an analysis window. By implementing customized texture model schemes, the TMR algorithm has the flexibility to characterize subsurface geology for different purposes. A texture model with a constant phase is effective at enhancing the visibility of seismic structural fabrics, a texture model with a variable phase is helpful for visualizing seismic facies, and a texture model with variable amplitude, frequency, and size is instrumental in calibrating seismic to reservoir properties. Preliminary test case studies in the very recent past have indicated that the latest developments in seismic texture analysis have added to the existing amplitude interpretation theories and methodologies. These and future developments in seismic texture theory and methodologies will hopefully lead to a better understanding of the geologic implications of the seismic texture concept and to an improved geologic interpretation of reflection seismic amplitude

58 GEOSCIENCES↗