Results for “Level set methods” — Page 23

NASA NTRSDate not supplied

CDC Bioreactor Configuration Method for Volume Level Control with Controlled Inlet and Outlet Flow

Environmental Control Life Support Systems and other microbiological biofilm studies often utilize small scale bioreactors. Among these options are the popular BioSurface CDC bioreactors, currently being utilized by Marshall Space Flight Center groups researching the impact of biofilms on life support systems. After a recent experimental regime, it was determined additional equipment could be added to augment the capabilities of the bioreactors. Previous research configurations such as ASTM E3161-21 relied on an outlet stream gravity draining from a side drain port located above sampling coupons. This limited applications to experimental conditions with a controlled inlet and uncontrolled outlet flow. With the introduction of a small single pole single throw (SPST) reed float switch and a peristaltic pump connected to the outlet drain and a chassis controller, the bioreactor is able to maintain a set level. The modification allows additional variables to be tested, including highly adjustable fill and flush cycles, bioreactor volume, draining and filling control. Once the configuration modifications were implemented through the installation of the new equipment, data was collected to ensure the stability of the level measurements. As the level control switch is a float switch, consideration was taken into account for effects of internal stirring speed, along with effects of inlet and outlet flow rate. Data presented in this study will illustrate the stability and effectiveness of the configuration changes in equipment made to the bioreactor. These configuration changes have demonstrated control method to conduct biofilm mitigation techniques for ECLSS hardware research. The controlled level capabilities allow for a constant drip feed flow rate into the bioreactors, a key aspect of the biofilm mitigation testing.

CDC Bioreactor↗

NASA NTRSDate not supplied

CDC Bioreactor Configuration Method for Volume Level Control with Controlled Inlet and Outlet Flow

Environmental Control Life Support Systems and other microbiological biofilm studies often utilize small scale bioreactors. Among these options are the popular BioSurface CDC bioreactors, currently being utilized by Marshall Space Flight Center groups researching the impact of biofilms on life support systems. After a recent experimental regime, it was determined additional equipment could be added to augment the capabilities of the bioreactors. Previous research configurations such as ASTM E3161-21 relied on an outlet stream gravity draining from a side drain port located above sampling coupons. This limited applications to experimental conditions with a controlled inlet and uncontrolled outlet flow. With the introduction of a small single pole single throw (SPST) reed float switch and a peristaltic pump connected to the outlet drain and a chassis controller, the bioreactor is able to maintain a set level. The modification allows additional variables to be tested, including highly adjustable fill and flush cycles, bioreactor volume, draining and filling control. Once the configuration modifications were implemented through the installation of the new equipment, data was collected to ensure the stability of the level measurements. As the level control switch is a float switch, consideration was taken into account for effects of internal stirring speed, along with effects of inlet and outlet flow rate. Data presented in this study will illustrate the stability and effectiveness of the configuration changes in equipment made to the bioreactor. These configuration changes have demonstrated control method to conduct biofilm mitigation techniques for ECLSS hardware research. The controlled level capabilities allow for a constant drip feed flow rate into the bioreactors, a key aspect of the biofilm mitigation testing.

CDC Bioreactor↗

NASA NTRSDate not supplied

CDC Bioreactor Configuration Method for Volume Level Control with Controlled Inlet and Outlet Flow

Environmental Control Life Support Systems and other microbiological biofilm studies often utilize small scale bioreactors. Among these options are the popular BioSurface CDC bioreactors, currently being utilized by Marshall Space Flight Center groups researching the impact of biofilms on life support systems. After a recent experimental regime, it was determined additional equipment could be added to augment the capabilities of the bioreactors. Previous research configurations such as ASTM E3161-21 relied on an outlet stream gravity draining from a side drain port located above sampling coupons. This limited applications to experimental conditions with a controlled inlet and uncontrolled outlet flow. With the introduction of a small single pole single throw (SPST) reed float switch and a peristaltic pump connected to the outlet drain and a chassis controller, the bioreactor is able to maintain a set level. The modification allows additional variables to be tested, including highly adjustable fill and flush cycles, bioreactor volume, draining and filling control. Once the configuration modifications were implemented through the installation of the new equipment, data was collected to ensure the stability of the level measurements. As the level control switch is a float switch, consideration was taken into account for effects of internal stirring speed, along with effects of inlet and outlet flow rate. Data presented in this study will illustrate the stability and effectiveness of the configuration changes in equipment made to the bioreactor. These configuration changes have demonstrated control method to conduct biofilm mitigation techniques for ECLSS hardware research. The controlled level capabilities allow for a constant drip feed flow rate into the bioreactors, a key aspect of the biofilm mitigation testing.

CDC Bioreactor↗

DOE OSTI2024

Low-Cost Heliostat for High-Flux Small-Area Receivers (Final Technical Report)

This project analyzed a two-stage heliostat concept consisting of a tracking stage and a concentrating stage. The tracking stage uses mirrors mounted on a common drive that move to track the sun. The concentrating stage consists of stationary mirrors that each have a unique angle to direct rays towards a small-area, high-flux, point-focused receiver. By splitting the collection and concentrating process into two stages, multiple small, inexpensive mirrors can share a structure and be controlled by a single drive in the tracking stage. The project effort developed modeling techniques that were specifically relevant to this two-stage heliostat concept. Both field-level and unit-level models were developed. The field-level model does not explicitly consider unit-level losses which are predicted by the unit-level model and then integrated into the field-level model through a correlation referred to as an efficiency modifier. This approach is referred to as the two-model approach; the development and demonstration of this two-model approach for a multi-stage heliostat technology is a key outcome of this work. The field-level model is used to design a field that hits a specific design day power given a set of heliostat design parameters. An oversized field is simulated and then heliostat units are removed based on their annual energy production in order to generate the highest performing field. The field reduction procedure fits a smooth curve fit to annual energy production as a function of position in the field which has the effect of reducing the noise that is otherwise caused by the Monte Carlo ray tracing technique. This approach is referred to as the annual energy fit method and substantially reduces computational run time for a given field level modeling accuracy. The annual energy fit approach enables the selection of a properly sized, high-performing field using orders of magnitude fewer rays than would otherwise be possible and the development of this approach is a second key outcome of this work. These models are used within a genetic optimization algorithm in order to optimize the geometric parameters associated with a heliostat in order to achieve the lowest cost per unit of collected design day power. The cost modeling that underlies the optimization is a simple, scaling type analysis backed up by a much more detailed Design for Manufacture and Assembly (DFMA) analysis. Although the figure of merit used for optimization was not cost per mirror area, this metric is reasonable to use as a means of comparison. The optimally designed 500 kW design has a tracking mirror specific cost of $181.85/m 2 , which is significantly larger than the target value and also larger than the current state of the art. The cost of the torque-tube type linkages contributed substantially to the overall cost. Based on this observation, potentially attractive alternative design configuration utilizing a capstan type actuation system should be investigated. Finally, NREL compared the performance of the two-stage heliostat to the performance of a focused and different sized flat conventional heliostats and showed that, as expected, additional losses versus the convention heliostat caused by a worse cosine efficiency, two stages of reflection, and interstage interactions. The two-stage heliostat requires around 75% more reflective area than a flat 1x1 meter conventional heliostat (similar to a focused heliostat) and 40% more than a flat 2x2 meter conventional heliostat.

14 SOLAR ENERGY↗

NASA NTRSDate not supplied

CDC Bioreactor Configuration Method for Volume Level Control with Controlled Inlet and Outlet Flow

Environmental Control Life Support Systems and other microbiological biofilm studies often utilize small scale bioreactors. Among these options are the popular BioSurface CDC bioreactors, currently being utilized by Marshall Space Flight Center groups researching the impact of biofilms on life support systems. After a recent experimental regime, it was determined additional equipment could be added to augment the capabilities of the bioreactors. Previous research configurations such as ASTM E3161 – 18 relied on an outlet stream gravity draining from a side drain port located above sampling coupons. This limited applications to experimental conditions with a controlled inlet and uncontrolled outlet flow. With the introduction of a small single pole single throw (SPST) reed float switch, a peristaltic pump connected to the outlet drain and a chassis controller, the bioreactor is able to maintain a set level. The modification allows additional variables to be tested, including highly adjustable fill and flush cycles, bioreactor volume, draining and filling control. Once the configuration modifications were implemented through the installation of the new equipment, data was collected to ensure the stability of the level measurements. As the level control switch is a float switch, consideration was taken into account for effects of internal stirring speed, along with effects of inlet and outlet flow rate. Data presented in this study will illustrate the stability and effectiveness of the configuration changes in equipment made to the bioreactor. These configuration changes are proving an effective control method to conduct biofilm mitigation techniques for ECLSS hardware research. The controlled level capabilities allow for a constant drip feed flow rate into the bioreactors, a key aspect of the biofilm mitigation testing.

CDC Bioreactor↗

DOE OSTI2025

Contaminant Investigation and Pre‐Processing Opportunities for Textile‐To‐Textile Recycling

Millions of metric tons of textiles are landfilled or incinerated each year in the United States, with less than 1% of textiles recycled into new clothing or fabrics. To counter this trend, a growing number of companies and researchers are exploring how a circular economy can be applied to support textile‐to‐textile recycling. A significant barrier they face comes down to quickly and efficiently extracting pure feedstock material from post‐consumer garments that feature a mix of natural and synthetic fibers. Textile recyclers prefer pure feedstocks, as working with mixed sources typically means lower throughput, higher risk of equipment failure, and diminished business margins. To facilitate a circular economy for textiles, methods, and technologies are needed that can efficiently separate out materials and contaminants from end‐of‐life textiles to increase the flow of pure feedstocks to recyclers. This paper summarizes findings from interviews with a cross section of textile recyclers and from a review of literature to define basic feedstock requirements. In addition to our qualitative research, we deconstruct a bale of post‐consumer textiles and analyze them using computer‐vision imaging, Fourier transform infrared spectroscopy (FTIR), and machine learning. The resulting data are used to set system‐level design inputs for an automated contaminant removal system to process post‐consumer clothing into appropriate feedstocks for recycling. To set the system's levels for automated real‐time near‐infrared analysis, we identify the minimum percentage of primary material that any single garment in a load of used clothing must contain for the average of the full output stream to meet the target purity levels of recyclers. Here, the envisioned automated system can also address undesirable trace materials that might contaminate the processed stream by using imaging cameras coupled with artificial intelligence to identify sections of clothing for de‐trimming. Proof‐of‐concept machine learning algorithms are evaluated to locate and identify trims or garment areas with hidden contaminant materials. Integrating these methods into automated textile cutting systems can provide a cost‐effective means for increasing feedstock purity from used clothing, which can advance circularity for textiles by helping recyclers to reach production volumes and quality targets that were not possible solely with manual dismantling operations.

Parsons, Ryan [Rochester Institute of Technology, ↗

DOE OSTI2026

Understanding Isomeric Effects on Properties of Aviation Fuels via a Group Contribution Method: Preprint

The molecular composition of aviation fuels, including conventional and sustainable aviation fuels (SAFs), significantly influences their performance, safety, and environmental impact. This study examines the effect of isomeric variation for compounds with the same carbon number and chemical family on key fuel properties, focusing on compounds commonly found in conventional jet fuels and SAFs. A group contribution method (GCM) is employed to predict thermophysical and combustion properties, providing an efficient analytical approach to evaluate the contributions of individual compounds to overall fuel mixture behavior. As part of this work, we introduce FuelLib, an open-source Python tool built around the GCM, to calculate individual compound and fuel mixture properties using various mixing rules. Our work evaluates whether the GCM can capture isomeric effects, that are often overlooked in traditional fuel property estimation. This is particularly important for SAFs, which often are composed of a more limited set of compound classes than conventional fuels, making isomeric differences more critical. Two-dimensional gas chromatography (GCxGC) data, which can be obtained from small fuel samples, provides weight percentages of compounds grouped by chemical family and carbon number rather than detailed information about individual compounds. As a result, assumptions must be made when decomposing GCxGC data into functional groups for GCM applications. Using GCxGC data, we show that the FuelLib tool can be used to predict the fuel properties of conventional jet fuels, with validation against experimental data. The provided tool enables researchers to predict fuel properties of candidate fuels and supports the design of new SAFs at both the component and mixture levels. This capability provides a foundation for studying fuel and combustion properties during SAF development, reducing reliance on costly experimental methods and advancing progress toward certification of new SAFs.The molecular composition of aviation fuels, including conventional and sustainable aviation fuels (SAFs), significantly influences their performance, safety, and environmental impact. This study examines the effect of isomeric variation for compounds with the same carbon number and chemical family on key fuel properties, focusing on compounds commonly found in conventional jet fuels and SAFs. A group contribution method (GCM) is employed to predict thermophysical and combustion properties, providing an efficient analytical approach to evaluate the contributions of individual compounds to overall fuel mixture behavior. As part of this work, we introduce FuelLib, an open-source Python tool built around the GCM, to calculate individual compound and fuel mixture properties using various mixing rules. Our work evaluates whether the GCM can capture isomeric effects, that are often overlooked in traditional fuel property estimation. This is particularly important for SAFs, which often are composed of a more limited set of compound classes than conventional fuels, making isomeric differences more critical. Two-dimensional gas chromatography (GCxGC) data, which can be obtained from small fuel samples, provides weight percentages of compounds grouped by chemical family and carbon number rather than detailed information about individual compounds. As a result, assumptions must be made when decomposing GCxGC data into functional groups for GCM applications. Using GCxGC data, we show that the FuelLib tool can be used to predict the fuel properties of conventional jet fuels, with validation against experimental data. The provided tool enables researchers to predict fuel properties of candidate fuels and supports the design of new SAFs at both the component and mixture levels. This capability provides a foundation for studying fuel and combustion properties during SAF development, reducing reliance on costly experimental methods and advancing progress toward certification of new SAFs.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1980

The Mark 3 data base handler

A data base handler which would act to tie Mark 3 system programs together is discussed. The data base handler is written in FORTRAN and is implemented on the Hewlett-Packard 21MX and the IBM 360/91. The system design objectives were to (1) provide for an easily specified method of data interchange among programs, (2) provide for a high level of data integrity, (3) accommodate changing requirments, (4) promote program accountability, (5) provide a single source of program constants, and (6) provide a central point for data archiving. The system consists of two distinct parts: a set of files existing on disk packs and tapes; and a set of utility subroutines which allow users to access the information in these files. Users never directly read or write the files and need not know the details of how the data are formatted in the files. To the users, the storage medium is format free. A user does need to know something about the sequencing of his data in the files but nothing about data in which he has no interest.

Ryan, J. W.↗

NASA NTRS1981

Evaluation of the procedure 1A component of the 1980 US/Canada wheat and barley exploratory experiment

Several techniques which use clusters generated by a new clustering algorithm, CLASSY, are proposed as alternatives to random sampling to obtain greater precision in crop proportion estimation: (1) Proportional Allocation/relative count estimator (PA/RCE) uses proportional allocation of dots to clusters on the basis of cluster size and a relative count cluster level estimate; (2) Proportional Allocation/Bayes Estimator (PA/BE) uses proportional allocation of dots to clusters and a Bayesian cluster-level estimate; and (3) Bayes Sequential Allocation/Bayesian Estimator (BSA/BE) uses sequential allocation of dots to clusters and a Bayesian cluster level estimate. Clustering in an effective method in making proportion estimates. It is estimated that, to obtain the same precision with random sampling as obtained by the proportional sampling of 50 dots with an unbiased estimator, samples of 85 or 166 would need to be taken if dot sets with AI labels (integrated procedure) or ground truth labels, respectively were input. Dot reallocation provides dot sets that are unbiased. It is recommended that these proportion estimation techniques are maintained, particularly the PA/BE because it provides the greatest precision.

Chapman, G. M.↗

NASA NTRS1988

Effect of advanced rotorcraft airfoil sections on the hover performance of a small-scale rotor model

A hover test was conducted on a small scale rotor model for two sets of tapered rotor blades. The baseline rotor blade set used a NACA 0012 airfoil section, whereas the second rotor blade set had advanced rotorcraft airfoils distributed along the radius. The experiment was conducted for a range of thrust coefficients and tip speeds, and the data were compared to the predictions of three analytical methods. The data show the advantage of the advanced airfoils at the higher rotor thrust levels; two of the analyses predicted the correct data trends.

Althoff, Susan L.↗

NASA NTRS2020

Measurements of few-mode fiber photonic lanterns in emulated atmospheric conditions for a low earth orbit space to ground optical communication receiver application

Photonic lanterns are being evaluated as a component of a scalable photon counting real-time optical ground receiver for space-to-ground photon-starved communication applications. The function of the lantern as a component of a receiver is to efficiently couple and deliver light from the atmospherically distorted focal spot formed behind a telescope to multiple small-core fiber-coupled single-element super-conducting nanowire detectors. This architecture solution is being compared to a multimode fiber coupled to a multi-element detector array. This paper presents a set of measurements that begins this comparison. This first set of measurements are a comparison of the throughput coupling loss at emulated atmospheric conditions for the case of a 60 cm diameter telescope receiving light from a low earth orbit satellite. The atmospheric conditions are numerically simulated at a range of turbulence levels using a beam propagation method and are physically emulated with a spatial light modulator. The results show that for the same number of output legs as the single-mode fiber lantern, the few-mode fiber lantern increases the power throughput up to 3.92 dB at the worst emulated atmospheric conditions tested of D/r(sub 0)=8.6. Furthermore, the coupling loss of the few-mode fiber lantern approaches the capability of a 30 micron graded index multimode fiber chosen for coupling to a 16 element detector array.

Tedder, Sarah A.↗

NASA NTRS2020

Measurements of Few-Mode Fiber Photonic Lanterns in Emulated Atmospheric Conditions for a Low Earth Orbit Space to Ground Optical Communication Receiver Application

Photonic lanterns are being evaluated as a component of a scalable photon counting real-time optical ground receiver for space-to-ground photon-starved communication applications. The function of the lantern as a component of a receiver is to efficiently couple and deliver light from the atmospherically distorted focal spot formed behind a telescope to multiple small-core fiber-coupled single-element super-conducting nanowire detectors. This architecture solution is being compared to a multimode fiber coupled to a multi-element detector array. This paper presents a set of measurements that begins this comparison. This first set of measurements are a comparison of the throughput coupling loss at emulated atmospheric conditions for the case of a 60 cm diameter telescope receiving light from a low earth orbit satellite. The atmospheric conditions are numerically simulated at a range of turbulence levels using a beam propagation method and are physically emulated with a spatial light modulator. The results show that for the same number of output legs as the single-mode fiber lantern, the few mode fiber lantern increases the power throughput up to 3.92 dB at the worst emulated atmospheric conditions tested of D/r0=8.6. Furthermore, the coupling loss of the few mode fiber lantern approaches the capability of a 30 micron graded index multimode fiber chosen for coupling to a 16 element detector array.

Tedder, Sarah A.↗

NASA NTRSDate not supplied

Post-Flight Performance Analysis of Navigation and Advanced Guidance Algorithms on a Terrestrial Suborbital Rocket Flight

There is currently renewed interest in robotic and crewed landers for a return to the lunar surface. Advanced guidance and navigation algorithms are essential to accurately delivering cargo and crew safely to the moon successfully. This paper reports the overall performance of an integrated set of navigation and guidance algorithms flown on a terrestrial suborbital rocket up to an altitude of approximately 100km. The navigation algorithm consists of an onboard extended Kalman Filter (EKF) that ingests multiple sensor measurements, one of which is the output from a terrain relative navigation (TRN) algorithm that cross-references camera images to on-board satellite imagery to perform feature correlation within the camera image. The guidance algorithm solves for a 6-degree-of-freedom (DoF) optimal trajectory using a successive convexification method during powered descent. The altitude range as well as the landing dynamics experienced during this test flight are realistic for an extraterrestrial landing and provide an invaluable data set to gauge the current development of these landing algorithms in an effort to advance the overall software readiness levels (SRL). This paper will delve into different aspects of each algorithm and present an analysis of the in-flight performance of the algorithms. This flight was conducted under the National Aeronautics and Space Administration (NASA) Safe and Precise Landing Integrated Capabilities Evolution (SPLICE) project focused on technology advancement for landing applications.

Guidance↗

NASA NTRS2010

Summary of the Fourth AIAA CFD Drag Prediction Workshop

Results from the Fourth AIAA Drag Prediction Workshop (DPW-IV) are summarized. The workshop focused on the prediction of both absolute and differential drag levels for wing-body and wing-body-horizontal-tail configurations that are representative of transonic transport air- craft. Numerical calculations are performed using industry-relevant test cases that include lift- specific flight conditions, trimmed drag polars, downwash variations, dragrises and Reynolds- number effects. Drag, lift and pitching moment predictions from numerous Reynolds-Averaged Navier-Stokes computational fluid dynamics methods are presented. Solutions are performed on structured, unstructured and hybrid grid systems. The structured-grid sets include point- matched multi-block meshes and over-set grid systems. The unstructured and hybrid grid sets are comprised of tetrahedral, pyramid, prismatic, and hexahedral elements. Effort is made to provide a high-quality and parametrically consistent family of grids for each grid type about each configuration under study. The wing-body-horizontal families are comprised of a coarse, medium and fine grid; an optional extra-fine grid augments several of the grid families. These mesh sequences are utilized to determine asymptotic grid-convergence characteristics of the solution sets, and to estimate grid-converged absolute drag levels of the wing-body-horizontal configuration using Richardson extrapolation.

Vassberg, John C.↗

NASA NTRS2012

Evaluating Suit Fit Using Performance Degradation

The Mark III planetary technology demonstrator space suit can be tailored to an individual by swapping the modular components of the suit, such as the arms, legs, and gloves, as well as adding or removing sizing inserts in key areas. A method was sought to identify the transition from an ideal suit fit to a bad fit and how to quantify this breakdown using a metric of mobility-based human performance data. To this end, the degradation of the range of motion of the elbow and wrist of the suit as a function of suit sizing modifications was investigated to attempt to improve suit fit. The sizing range tested spanned optimal and poor fit and was adjusted incrementally in order to compare each joint angle across five different sizing configurations. Suited range of motion data were collected using a motion capture system for nine isolated and functional tasks utilizing the elbow and wrist joints. A total of four subjects were tested with motions involving both arms simultaneously as well as the right arm by itself. Findings indicated that no single joint drives the performance of the arm as a function of suit size; instead it is based on the interaction of multiple joints along a limb. To determine a size adjustment range where an individual can operate the suit at an acceptable level, a performance detriment limit was set. This user-selected limit reveals the task-dependent tolerance of the suit fit around optimal size. For example, the isolated joint motion indicated that the suit can deviate from optimal by as little as -0.6 in to -2.6 in before experiencing a 10% performance drop in the wrist or elbow joint. The study identified a preliminary method to quantify the impact of size on performance and developed a new way to gauge tolerances around optimal size.

Margerum, Sarah E.↗

NASA NTRSDate not supplied

Automation of the Uncertainty Quantification Process Based on Probability Boxes with DAKOTA

To date, while the use of CFD is prevalent, very few efforts have been undertaken that truly attempt to document all (or even most) of the sources of uncertainty in the simulations. Instead, the current state-of-the-art relies heavily on the experience of the CFD practitioner to estimate the uncertainty associated with their simulations through simple sensitivity studies or subject matter expertise. This practice will have to be replaced with a formal uncertainty quantification (UQ) process if CFD is to play an expanded role in the design research and engineering community, test and evaluation community, and ultimately certification for flight. This is especially true for hypersonic air-breathing propulsion systems due to the environment, scale, and duration limitations of ground test facilities. Accounting for uncertainties in a formal manner is a tedious process. Moreover, the typical CFD practitioner is not likely to be familiar with formal UQ methods. Hence, a major obstacle that has prevented the adoption of UQ methods for engineering design and development work is the lack of a tool set to automate most (if not all) of the UQ workflow. Towards this end, the SANDIA package DAKOTA (which has been developed to drive both UQ and optimization processes) will be tightly wrapped around the VULCAN-CFD code to automate the uncertainty quantification process. The automated process will be applied to an isolator turbulence model validation exercise that has previously been documented using a manual approach to the UQ process. Hence, the focus of this paper will be documenting the level to which automation can hide the UQ process details from the CFD practitioner rather than the UQ method itself.

CFD↗

DOE OSTI2024

Towards verifiable cancer digital twins: tissue level modeling protocol for precision medicine

Cancer exhibits substantial heterogeneity, manifesting as distinct morphological and molecular variations across tumors, which frequently undermines the efficacy of conventional oncological treatments. Developments in multiomics and sequencing technologies have paved the way for unraveling this heterogeneity. Nevertheless, the complexity of the data gathered from these methods cannot be fully interpreted through multimodal data analysis alone. Mathematical modeling plays a crucial role in delineating the underlying mechanisms to explain sources of heterogeneity using patient-specific data. Intra-tumoral diversity necessitates the development of precision oncology therapies utilizing multiphysics, multiscale mathematical models for cancer. This review discusses recent advancements in computational methodologies for precision oncology, highlighting the potential of cancer digital twins to enhance patient-specific decision-making in clinical settings. We review computational efforts in building patient-informed cellular and tissue-level models for cancer and propose a computational framework that utilizes agent-based modeling as an effective conduit to integrate cancer systems models that encode signaling at the cellular scale with digital twin models that predict tissue-level response in a tumor microenvironment customized to patient information. Furthermore, we discuss machine learning approaches to building surrogates for these complex mathematical models. These surrogates can potentially be used to conduct sensitivity analysis, verification, validation, and uncertainty quantification, which is especially important for tumor studies due to their dynamic nature.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

Learning Molecular Mixture Property Using Chemistry-Aware Graph Neural Network

Recent advances in machine learning (ML) are expediting materials discovery and design. One significant challenge facing ML for materials is the expansive combinatorial space of potential materials formed by diverse constituents and their flexible configurations. This complexity is particularly evident in molecular mixtures, a frequently explored space for materials, such as battery electrolytes. Owing to the complex structures of molecules and the sequence-independent nature of mixtures, conventional ML methods have difficulties in modeling such systems. Here, we present MolSets, a specialized ML model for molecular mixtures, to overcome the difficulties. Representing individual molecules as graphs and their mixture as a set, MolSets leverages a graph neural network and the deep sets architecture to extract information at the molecular level and aggregate it at the mixture level, thus addressing local complexity while retaining global flexibility. We demonstrate the efficacy of MolSets in predicting the conductivity of lithium battery electrolytes and highlight its benefits in the virtual screening of the combinatorial chemical space. Published by the American Physical Society 2024

Zhang, Hengrui (ORCID:0000000231831654)↗