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At least 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

A Dimensionally Aligned Signal Projection for Classification of Unintended Radiated Emissions

Characterization of unintended radiated emissions (URE) from electronic devices plays an important role in many research areas from electromagnetic interference to nonintrusive load monitoring to information system security. URE can provide insights for applications ranging from load disaggregation and energy efficiency to condition-based maintenance of equipment-based upon detected fault conditions. URE characterization often requires subject matter expertise to tailor transforms and feature extractors for the specific electrical devices of interest. We present a novel approach, named dimensionally aligned signal projection (DASP), for projecting aligned signal characteristics that are inherent to the physical implementation of many commercial electronic devices. These projections minimize the need for an intimate understanding of the underlying physical circuitry and significantly reduce the number of features required for signal classification. We present three possible DASP algorithms that leverage frequency harmonics, modulation alignments, and frequency peak spacings, along with a two-dimensional image manipulation method for statistical feature extraction. To demonstrate the ability of DASP to generate relevant features from URE, we measured the conducted URE from 14 residential electronic devices using a 2 MS/s collection system. Furthermore, a linear discriminant analysis classifier was trained using DASP generated features and was blind tested resulting in a greater than 90% classification accuracy for each of the DASP algorithms and an accuracy of 99.1% when DASP features are used in combination. Furthermore, we show that a rank reduced feature set of the combined DASP algorithms provides a 98.9% classification accuracy with only three features and outperforms a set of spectral features in terms of general classification as well as applicability across a broad number of devices.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1993

Imaging the sun in hard x rays using Fourier telescopes

For several years, solar flares have been observed with a variety of instruments confirming that tremendous amounts of energy are locally stored in the solar magnetic field and then rapidly released during the life of the flare. In concert with observations, theorists have attempted to describe the means by which these energetic events occur and evolve. Two competing theories have emerged and have stood the test of time. One theory describes the flare in terms of nonthermal, electron beam injection into a thick target while the other uses a thermal approach. Both theories provide results which are reasonably consistent with current observations; but to date, none have been able to provide conclusive evidence as to the validity of either model. Imaging on short time scales (1 s) and/or small size scales (1 arc s) should give definitive answers to these questions. In order to test whether a realistic telescope can indeed discriminate between models, we construct model sources based upon the thermal and the nonthermal models and calculate the emission as a function of time and energy in the range from 10 to 100 keV. In addition, we construct model telescopes representing both the spatial modulation collimator (SMC) and the rotating modulation collimator (RMC) techniques of observation using random photon counting statistics. With these two types of telescopes we numerically simulate the instrument response to the above two model flares to see if there are distinct x-ray signatures which may be discernable. We find that theoretical descriptions of the primary models of solar flares do indeed predict different hard x-ray signatures for 1 sec time scales and at 1-5 arc sec spatial resolution. However, these distinguishing signatures can best be observed early in the impulsive phase and from a position perpendicular to the plane of the loop. Furthermore, we find that Fourier telescopes with reasonable and currently attainable design characteristics can image these signatures and that the same sensitive areas and short temporal integration times relative to source evolution (i.e., 1 s), the RMC and the SMC will both provide about the same performance.

Campbell, J. W.↗
DOE OSTI2018

Method of Determining the Reliability of Real-Time In-reactor Monitoring of VVER

A methodological approach and the basic tenets for evaluating the reliability of in-reactor monitoring of VVER are presented. The method is based on the statistical analysis of indications in real time and includes methods for evaluating the admissible maximum error of the measurement channels used for monitoring as well as the average value and admissible deviation of indications in groups of parallel monitoring channels, as well as a method of evaluating reliability by comparing the values of a parameter with the regime values. In comparing the indications of a monitoring channel with the indications of other parallel channels, the median value is proposed as the baseline value. The developed method is implemented in the Diagnostika SVRK special software, which has been successfully tested during the commissioning of the No. 1 unit at the Novovoronezh NPP-2.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2019

Estimation of Tropical Cyclone Intensity in the North Atlantic and Northeastern Pacific Basins Using TRMM Satellite Passive Microwave Observations

Here, a statistical passive microwave intensity estimation (PMW-IE) algorithm for estimating the intensity of tropical cyclones (TCs) in the North Atlantic and northeastern and central Pacific basins is developed and tested. The algorithm is derived from Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) 85-GHz brightness temperatures and near-surface rain-rate retrievals to provide objective estimates of current maximum sustained surface winds (Vmax) and 6-h future Vmax of TCs. The full record of TRMM data (1998–2013) including 2326 TMI overpasses of 503 TCs is separated into dependent samples (1998–2010) for model development and independent samples (2011–13) for model verification. The best track intensities are used as dependent variables in a stepwise multiple-regression approach. Separately for each basin, three regression models are derived using selected 1) 85-GHz-only variables, 2) rain-rate-only variables, and 3) combined 85-GHz and rain variables. The algorithms are assessed using independent samples and those with contemporaneous aircraft-reconnaissance measurements. Rain-only and combined models perform better than the 85-GHz-only model. Lower errors are found for estimating the 6-h future Vmax than estimating the current Vmax using all three models. This implies that it is optimal to use passive-microwave-retrieved rain variables observed a few hours earlier to estimate TC intensity. The MAE (RMSE) of 6-h future Vmax is 9 (12) kt (1 kt ≈ 0.51 m s -1 ) when testing the combined models with ATL and EPA independent samples. Aircraft-reconnaissance-based independent samples yields a MAE of 9.6 kt and RMSE of 12.6 kt for estimating 6-h future Vmax.

58 GEOSCIENCES↗
DOE OSTI2024

The relationship between stress, anxiety and eating behavior among Chinese students: a cross-sectional study

Background The expansion of higher education and the growing number of college students have led to increased awareness of mental health issues such as stress, anxiety, and eating disorders. In China, the educational system and cultural expectations contribute to the stress experienced by college students. This study aims to clarify the role of anxiety as a mediator in the relationship between stress and eating behaviors among Chinese college students. Methods This study utilized data from the 2021 Psychology and Behavior Investigation of Chinese Residents, which included 1,672 college students under the age of 25. The analysis methods comprised descriptive statistics, t -tests, Pearson correlation analyses, and mediation effect analysis. Results The findings indicate that Chinese college students experience high levels of stress, with long-term stress slightly exceeding short-term stress. Both types of stress were positively correlated with increased anxiety and the adoption of unhealthy eating behaviors. Anxiety was identified as a significant mediator, accounting for 28.3% of the relationship between long-term stress and eating behavior (95% CI = 0.058–0.183). The mediation effect of short-term stress on eating behavior through anxiety was also significant, explaining 61.4% of the total effect (95% CI = 0.185–0.327). Conclusion The study underscores the importance of stress management and mental health services for college students. It recommends a comprehensive approach to reducing external pressures, managing anxiety, and promoting healthy eating behaviors among college students. Suggestions include expanding employment opportunities, providing career guidance, enhancing campus and societal support for holistic development, strengthening mental health services, leveraging artificial intelligence technologies, educating on healthy lifestyles, and implementing targeted health promotion programs.

Chai, Yulin↗
NASA NTRSDate not supplied

Setting the Bar for the Replacement of the Probability of Collision Metric

To date, satellite conjunction assessment (CA) risk analysis has largely embraced the probability of collision (Pc) as the omnibus metric to evaluate collision likelihood, and its use in such assessments has mostly been straightforward: at the point at which a conjunction mitigation decision is required, the calculated Pc is compared to a threshold; and if the calculated Pc exceeds that threshold, then a mitigation action is warranted. With only minor variation, this approach is employed by major CA risk assessment centers (e.g., NASA, EUSST, CNES, JAXA) and is advanced as the preferred method in the published CA best practices handbooks. Despite this near unanimity of operational practice, there is a major strain of secondary literature critical of the Pc and willing to propose alternatives. Alfano (2005) pointed out the ability of the Pc to underrepresent the risk in certain situations and counselled a maximum Pc construct. Carpenter (2017, 2019) reiterated this criticism and proposed using instead a confidence interval on the miss distance. Balch et al. (2019) identified what they argued was a defect in the entire Bayesian Pc construct and believed that the use of a more conservative methodology based on covariance ellipsoid overlap was necessary. Delande (2022) introduced the framework of collision “plausibility” to the risk assessment process and sketched out how this might be used operationally. Elkantassi (2022) published a full development of the miss distance confidence interval approach and applied it to several worked examples. While these different approaches to collision risk assessment do differ in their details, they all converge on two central points: first, the Pc’s failure to give an adequate expression of the risk in dilution region situations is a fatal flaw; and second, a conjunction should be presumed risky and in need of mitigation until the evidence of the situation can establish otherwise. These criticisms, if correct, would counsel a number of modifications to current CA operational practice; as such, they force a re-examination of fundamental aspects of the CA problem, including the following: 1. Is the CA risk assessment a probability problem, a statistics problem, or something else? 2. If it is a statistics problem, does it lend itself naturally to a hypothesis test construction? 3. If it can be construed as a hypothesis test, what form should the null hypothesis take, to wit: what constraints exist on the choice of the null hypothesis, what selections are in best alignment with all of the attendant parameters of the problem, and what is implied philosophically by different choices? 4. What are the implications of using the different proposed risk assessment parameters for CA? This question should be answered both in determining how frequently the dilution region situation cited by the critics of the Pc actually appears in an operationally significant manner and the missed detection and false alarm rates of all of the proposed risk assessment metrics, compared both to the Pc and to each other. This paper explores and offers preliminary answers to the above questions, presenting a researched treatment of the philosophical nature of the CA problem and the null hypothesis choice that achieves the greatest consistency with all of the different aspects of operational CA conduct. It then profiles all of the different proposed risk assessment metrics enumerated in the earlier paragraph against an extremely large database of conjunction events at both the 550km and 700km altitudes. The combination of the philosophical exploration of the CA problem and the results of the profiling activity articulates what a risk assessment metric will need to demonstrate, in terms of both innate construction and performance, in order to be a true competitor to the Pc.

conjunction assessment↗
DOE OSTI2018

A Ricin Forensic Profiling Approach Based on a Complex Set of Biomarkers

A forensic method for the retrospective determination of preparation methods used for illicit ricin toxin production was developed. The method was based on a complex set of biomarkers, including carbohydrates, fatty acids, seed storage proteins, in combination with data on ricin and Ricinus communis agglutinin. The analyses were performed on samples prepared from four castor bean plant ( Ricinus communis ) cultivars by four different sample preparation methods (PM1 – PM4) ranging from simple disintegration of the castor beans to multi-step preparation methods including different protein precipitation methods. Comprehensive analytical data was collected by use of a range of analytical methods and robust orthogonal partial least squares-discriminant analysis- models (OPLS-DA) were constructed based on the calibration set. By the use of a decision tree and two OPLS-DA models, the sample preparation methods of a test set of ricin preparations were determined. The model statistics of the two models were good and a 100% rate of correct predictions of the test set was achieved.

Fredriksson, Sten-Åke (ORCID:0000000237131990)↗
DOE OSTI2018

Hybrid feature selection approach for power transformer fault diagnosis based on support vector machine and genetic algorithm

To further improve fault diagnosis accuracy, a new hybrid feature selection approach combined with a genetic algorithm (GA) and support vector machine (SVM) is presented in this study. Adaptive synthetic technique and arctangent transformation method are adopted to improve the statistical property of the training set (IEC TC10 dataset). Five filter methods based on different evaluation metrics are employed to rank 48 input features derived from dissolved gas analysis (DGA). Then, feature combination methods are applied to aggregate feature ranks and form a lower-dimension candidate feature subset. The GA-SVM model is implemented to optimise parameters and select optimal feature subsets. 5-fold cross-validation accuracy of the GA-SVM is used to evaluate fault diagnosis capability of feature subsets and finally, a novel subset is determined as the optimal feature subset. Accuracy comparison manifests the superiority of the optimal feature subsets over that of conventional approaches. Besides, generalisation and robustness of the optimal subset are validated by testing DGA samples from the local power utility. Results indicate that the optimal feature subset obtained by the proposed method can significantly improve the accuracies of power transformer fault diagnosis.

Kari, Tusongjiang↗
NASA NTRS2000

Quantum Interferometry

Recently, several researchers, including yours truly, have been able to demonstrate theoretically that quantum photon entanglement has the potential to also revolutionize the entire field of optical interferometry, by providing many orders of magnitude improvement in interferometer sensitivity. The quantum entangled photon interferometer approach is very general and applies to many types of interferometers. In particular, without nonlocal entanglement, a generic classical interferometer has a statistical-sampling shot-noise limited sensitivity that scales like 1/Sqrt[N], where N is the number of particles (photons, electrons, atoms, neutrons) passing through the interferometer per unit time. However, if carefully prepared quantum correlations are engineered between the particles, then the interferometer sensitivity improves by a factor of Sqrt[N] (square root of N) to scale like 1/N, which is the limit imposed by the Heisenberg Uncertainty Principle. For optical (laser) interferometers operating at milliwatts of optical power, this quantum sensitivity boost corresponds to an eight-order-of-magnitude improvement of signal to noise. Applications are to tests of General Relativity such as ground and orbiting optical interferometers for gravity wave detection, Laser Interferometer Gravity Observatory (LIGO) and the European Laser Interferometer Space Antenna (LISA), respectively.

Dowling, Jonathan P.↗
NASA NTRS2008

The NASA Robotic Conjunction Assessment Process: Overview and Operational Experiences

Orbital debris poses a significant threat to spacecraft health and safety. Recent events such as China's anti-satellite test and the Breeze-M rocket explosion have led to an even greater awareness and concern in the satellite community. Therefore, the National Aeronautics and Space Administration (NASA) has established requirements that routine conjunction assessment screening shall be performed for all maneuverable spacecraft having perigees less than 2000 km or within 200 km of geosynchronous altitude. NASA s Goddard Space Flight Center (GSFC) has developed an operational collision risk assessment process to protect NASA s high-value unmanned (robotic) assets that has been in use since January 2005. This paper provides an overview of the NASA robotic conjunction assessment process, including descriptions of the new tools developed to analyze close approach data and of the risk mitigation strategies employed. In addition, statistical data describing the number of conjunctions experienced are presented. A debris avoidance maneuver performed by Aura in June of 2008 is described in detail to illustrate the process.

Newman, Lauri Kraft↗
NASA NTRS2009

A Methodology for Determining Statistical Performance Compliance for Airborne Doppler Radar with Forward-Looking Turbulence Detection Capability

The objective of the research developed and presented in this document was to statistically assess turbulence hazard detection performance employing airborne pulse Doppler radar systems. The FAA certification methodology for forward looking airborne turbulence radars will require estimating the probabilities of missed and false hazard indications under operational conditions. Analytical approaches must be used due to the near impossibility of obtaining sufficient statistics experimentally. This report describes an end-to-end analytical technique for estimating these probabilities for Enhanced Turbulence (E-Turb) Radar systems under noise-limited conditions, for a variety of aircraft types, as defined in FAA TSO-C134. This technique provides for one means, but not the only means, by which an applicant can demonstrate compliance to the FAA directed ATDS Working Group performance requirements. Turbulence hazard algorithms were developed that derived predictive estimates of aircraft hazards from basic radar observables. These algorithms were designed to prevent false turbulence indications while accurately predicting areas of elevated turbulence risks to aircraft, passengers, and crew; and were successfully flight tested on a NASA B757-200 and a Delta Air Lines B737-800. Application of this defined methodology for calculating the probability of missed and false hazard indications taking into account the effect of the various algorithms used, is demonstrated for representative transport aircraft and radar performance characteristics.

Bowles, Roland L.↗
NASA NTRSDate not supplied

Summary of the 6th AIAA Propulsion Aerodynamics Workshop Nozzle Test Case: Heated Supersonic Axisymmetric Jets

This paper summarizes findings from the sixth AIAA Propulsion Aerodynamics Workshop (PAW) nozzle test case. The focus of the workshop participants was turbulent supersonic round jets with variation in jet Mach number and jet heating. Three nozzles were utilized with on-design jet Mach numbers of 1.36, 1.63, and 2.00. A heated jet for each of these three nozzles at on-design conditions, a temperature matched on-design condition at Mach 1.63, and an off-design heated condition for the Mach 1.63 nozzle were the five cases examined. Workshop participants utilized Reynolds-averaged Navier-Stokes (RANS) and Large Eddy Simulation (LES) based techniques. Computational fluid dynamics (CFD) solutions were compared with non-intrusive measurements of velocities and temperatures, including both mean values and turbulence statistics. In general, the RANS approaches were unable to capture the trend of reduced mixing as the jet Mach number increased. Incorporation of compressibility corrections improved the agreement with experimental measurements in terms of trends with varying jet Mach number, but also increased the jet potential core lengths to be in worse agreement with data. RANS methods were able to reasonably capture trends of jet heating. The LES-based approaches as a whole were able to capture the effects of compressibility more accurately. Effects of jet heating were captured well by LES. None of the LES approaches introduced disturbances from the wall boundary layers of the nozzle into the jet mixing layer, which would affect the jet flow physics modeling in the initial part of the jet shear layer, but would be very computationally demanding.

supersonic jet↗
DOE OSTI2015

A method of surface marker location optimization for tumor motion estimation in lung stereotactic body radiation therapy

Purpose: Accurately localizing lung tumor localization is essential for high-precision radiation therapy techniques such as stereotactic body radiation therapy (SBRT). Since direct monitoring of tumor motion is not always achievable due to the limitation of imaging modalities for treatment guidance, placement of fiducial markers on the patient’s body surface to act as a surrogate for tumor position prediction is a practical alternative for tracking lung tumor motion during SBRT treatments. In this work, the authors propose an innovative and robust model to solve the multimarker position optimization problem. The model is able to overcome the major drawbacks of the sparse optimization approach (SOA) model. Methods: The principle-component-analysis (PCA) method was employed as the framework to build the authors’ statistical prediction model. The method can be divided into two stages. The first stage is to build the surrogate tumor matrix and calculate its eigenvalues and associated eigenvectors. The second stage is to determine the “best represented” columns of the eigenvector matrix obtained from stage one and subsequently acquire the optimal marker positions as well as numbers. Using 4-dimensional CT (4DCT) and breath hold CT imaging data, the PCA method was compared to the SOA method with respect to calculation time, average prediction accuracy, prediction stability, noise resistance, marker position consistency, and marker distribution. Results: The PCA and SOA methods which were both tested were on all 11 patients for a total of 130 cases including 4DCT and breath-hold CT scenarios. The maximum calculation time for the PCA method was less than 1 s with 64 752 surface points, whereas the average calculation time for the SOA method was over 12 min with 400 surface points. Overall, the tumor center position prediction errors were comparable between the two methods, and all were less than 1.5 mm. However, for the extreme scenarios (breath hold), the prediction errors for the PCA method were not only smaller, but were also more stable than for the SOA method. Results obtained by imposing a series of random noises to the surrogates indicated that the PCA method was much more noise resistant than the SOA method. The marker position consistency tests using various combinations of 4DCT phases to construct the surrogates suggested that the marker position predictions of the PCA method were more consistent than those of the SOA method, in spite of surrogate construction. Marker distribution tests indicated that greater than 80% of the calculated marker positions fell into the high cross correlation and high motion magnitude regions for both of the algorithms. Conclusions: The PCA model is an accurate, efficient, robust, and practical model for solving the multimarker position optimization problem to predict lung tumor motion during SBRT treatments. Due to its generality, PCA model can also be applied to other imaging guidance system whichever using surface motion as the surrogates.

60 APPLIED LIFE SCIENCES↗
NASA NTRS2009

A Biomechanical Approach to Assessing Hip Fracture Risk

Bone loss in microgravity is well documented, but it is difficult to quantify how declines in bone mineral density (BMD) contribute to an astronaut's overall risk of fracture upon return. This study uses a biomechanical approach to assessing hip fracture risk, or Factor of Risk (Phi), which is defined as the ratio of applied load to bone strength. All long-duration NASA astronauts from Expeditions 1-18 were included in this study (n=25), while crewmembers who flew twice (n=2) were treated as separate subjects. Bone strength was estimated based on an empirical relationship between areal BMD at the hip, as measured by DXA, and failure load, as determined by mechanical testing of cadaver femora. Fall load during a sideways fall was calculated from a previously developed biomechanical model, which takes into account body weight, height, gender, and soft tissue thickness overlying the lateral aspect of the hip that serves to attenuate the impact force. While no statistical analyses have been performed yet, preliminary results show that males in this population have a higher FOR than females, with a post- flight Phi of 0.87 and 0.36, respectively. FOR increases 5.1% from preflight to postflight, while only one subject crossed the fracture "threshold" of Phi = 1, for a total of 2 subjects with a postflight Phi > 1. These results suggest that men may be at greater risk for hip fracture due largely in part to their relatively thin soft tissue padding as compared to women, since soft tissue thickness has the highest correlation (R(exp 2)= .53) with FOR of all subject-specific parameters. Future work will investigate changes in FOR during recovery to see if baseline risk levels are restored upon return to 1-g activity. While dual x-ray absorptiometry (DXA) is the most commonly used clinical measure of bone health, it fails to provide compartment-specific information that is useful in assessing changes to bone quality as a result of microgravity exposure. Peripheral quantitative computed tomography (pQCT) accomplishes this by imaging transverse "slices" of the long bones. This project was a re-analysis of a 90 day bed rest study to determine if changes to cortical and trabecular compartments could be detected in the distal tibia with statistical significance using a new pQCT image analysis method. Nearly all changes in bone mineral density (BMD) and cross sectional area (CSA) measures were seen with statistical significance, with the exception of a change in cortical BMD. Total bone CSA increased by 1.1 % (p =0.01), cortical CSA decreased by - 5.6% (p<0.001) and trabecular CSA increased by 1.76% (p=0.007); the combination of which suggests bone resorption occurred at the endocortical surface in response to mechanical unloading by bed rest. Furthermore, total BMD and trabecular BMD decreased (-3.8%, p=0.001 and -2.8%, p =0.007, respectively), while decreases in cortical BMD failed to reach significance (-1.2%, p=0.07). Given that compartment-specific changes are seen with significance and are likely to influence bone strength, it is recommended that pQCT remain a standard measure used in bed rest because it provides a unique measure by which to better evaluate the efficacy of countermeasures to microgravity-induced bone loss.

Ellman, Rachel↗
DOE OSTI2023

Study of η(1405)/η(1475) in $J/\psi \to \gamma {K}_S^0{K}_S^0{\pi}^0$ decay

Using a sample of (10 . 09 ± 0 . 04) × 10 9 J/ψ decays collected with the BESIII detector, partial wave analyses of the decay $ J/\psi \to \gamma {K}_S^0{K}_S^0{\pi}^0$ are performed within the ${K}_S^0{K}_S^0{\pi}^0$ invariant mass region below 1.6 GeV/ c 2 . The covariant tensor amplitude method is used in both mass independent and mass dependent approaches. Both analysis approaches exhibit dominant pseudoscalar and axial vector components, and show good consistency for the other individual components. Furthermore, the mass dependent analysis reveals that the ${K}_S^0{K}_S^0{\pi}^0$ invariant mass spectrum for the pseudoscalar component can be well described with two isoscalar resonant states using relativistic Breit-Wigner model, i.e., the η (1405) with a mass of $1391.7\pm {0.7}_{-0.3}^{+11.3}$ MeV/ c 2 and a width of $60.8\pm {1.2}_{-12.0}^{+5.5}$ MeV, and the η (1475) with a mass of $1507.6\pm {1.6}_{-32.2}^{+15.5}$ MeV/ c 2 and a width of $115.8\pm {2.4}_{-10.9}^{+14.8}$ MeV. The first and second uncertainties are statistical and systematic, respectively. Alternate models for the pseudoscalar component are also tested, but the description of the ${K}_S^0{K}_S^0{\pi}^0$ invariant mass spectrum deteriorates significantly.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Prospects and Limitations of Predicting Fuel Ignition Properties from Low-Temperature Speciation Data

Using chemical kinetic modeling and statistical analysis, we investigate the possibility of correlating key chemical “markers”–typically small molecules–formed during very lean (φ ~ 0.001) oxidation experiments with near-stoichiometric (φ ~ 1) fuel ignition properties. One goal of this work is to evaluate the feasibility of designing a fuel-screening platform, based on small laboratory reactors that operate at low temperatures and use minimal fuel volume. Buras et al. [Combust. Flame2020,216, 472–484] have shown that convolutional neural net (CNN) fitting can be used to correlate first-stage ignition delay times (IDTs) with OH/HO2 measurements during very lean oxidation in low-T flow reactors with better than factor-of-2 accuracy. In this work, we test the limits of applying this correlation-based approach to predict the low-temperature heat release (LTHR) and total IDT, including the sensitivity of total IDT to the equivalence ratio, φ. We demonstrate that first-stage IDT can be reliably correlated with very lean oxidation measurements using compressed sensing (CS), which is simpler to implement than CNN fitting. LTHR can also be predicted via CS analysis, although the correlation quality is somewhat lower than for first-stage IDT. In contrast, the accuracy of total IDT prediction at φ = 1 is significantly lower (within a factor of 4 or worse). Furthermore, these results can be rationalized by the fact that the first-stage IDT and LTHR are primarily determined by low-temperature chemistry, whereas total IDT depends on low-, intermediate-, and high-temperature chemistry. Oxidation reactions are most important at low temperatures, and therefore, measurements of universal molecular markers of oxidation do not capture the full chemical complexity required to accurately predict the total IDT even at a single equivalence ratio. As a result, we find that φ-sensitivity of ignition delay cannot be predicted at all using solely correlation with lean low-T chemical speciation measurements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

SU-E-J-04: A Data-Driven, Response-Based, Multi-Criteria Decision Support System for Personalized Lung Radiation Treatment Planning

Purpose: To develop a decision support tool to predict a patient's potential overall survival (OS) and radiation induced toxicity (RIT) based on clinical factors and responses during the course of radiotherapy, and suggest appropriate radiation dose adjustments to improve therapeutic effect. Methods: Important relationships between a patient's basic information and their clinical features before and during the radiation treatment are identified from historical clinical data by using statistical learning and data mining approaches. During each treatment period, a data analysis (DA) module predicts radiotherapy features such as time to local progression (TTLP), time to distant metastases (TTDM), radiation toxicity to different organs, etc., under possible future treatment plans based on patient specifics or responses. An information fusion (IF) module estimates intervals for a patient's OS and the probabilities of RIT from a treatment plan by integrating the outcomes of module DA. A decision making (DM) module calculates “satisfaction” with the predicted radiation outcome based on trade-offs between OS and RIT, and finds the best treatment plan for the next time period via multi-criteria optimization. Results: Using physical and biological data from 130 lung cancer patients as our test bed, we were able to train and implement the 3 modules of our decision support tool. Examples demonstrate how it can help predict a new patient's potential OS and RIT with different radiation dose plans along with how these combinations change with dose, thus presenting a range of satisfaction/utility for use in individualized decision support. Conclusion: Although the decision support tool is currently developed from a small patient sample size, it shows the potential for the improvement of each patient's satisfaction in personalized radiation therapy. The radiation treatment outcome prediction and decision making model needs to be evaluated with more patients and demonstrated for use in radiation treatments for other cancers. P01-CA59827;R01CA142840.

60 APPLIED LIFE SCIENCES↗