Biological optimization systems for enhancing photosynthetic efficiency and methods of use
The present disclosure relates to biological optimization systems for enhancing photosynthetic efficiency and methods of use.
60 APPLIED LIFE SCIENCES↗
SEARCH · Engineering Papers
Results for “optimization methods”
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Rapid determination of 226 Ra in emergency urine samples
A new method has been developed at the Savannah River National Laboratory (SRNL) that can be used for the rapid determination of 226 Ra in emergency urine samples following a radiological incident. If a radiological dispersive device event or a nuclear accident occurs, there will be an urgent need for rapid analyses of radionuclides in urine samples to ensure the safety of the public. Large numbers of urine samples will have to be analyzed very quickly. This new SRNL method was applied to 100 mL urine aliquots, however this method can be applied to smaller or larger sample aliquots as needed. The method was optimized for rapid turnaround times; urine samples may be prepared for counting in <3 h. A rapid calcium phosphate precipitation method was used to pre-concentrate 226 Ra from the urine sample matrix, followed by removal of calcium by cation exchange separation. A stacked elution method using DGA Resin was used to purify the 226 Ra during the cation exchange elution step. This approach combines the cation resin elution step with the simultaneous purification of 226 Ra with DGA Resin, saving time. 133 Ba was used instead of 225 Ra as tracer to allow immediate counting; however, 225 Ra can still be used as an option. The rapid purification of 226 Ra to remove interferences using DGA Resin was compared with a slightly longer Ln Resin approach. A final barium sulfate micro-precipitation step was used with isopropanol present to reduce solubility; producing alpha spectrometry sources with peaks typically <40 keV FWHM (full width half max). This new rapid method is fast, has very high tracer yield (>90 %), and removes interferences effectively. The sample preparation method can also be adapted to ICP-MS measurement of 226 Ra, with rapid removal of isobaric interferences.
61 RADIATION PROTECTION AND DOSIMETRY↗
A Clustering-Based Scenario Generation Framework for Power Market Simulation with Wind Integration
A critical step in stochastic optimization models of power system analysis is to select a set of appropriate scenarios and significant numbers of scenario generation methods exist in the literature. This paper develops a clustering based scenario generation method, which aims to improve the performance of existing scenario generation techniques by grouping a set of correlated wind sites into clusters according to their cross-correlations. Copula based models are utilized to model spatiotemporal correlations and the Gibbs sampling is then used to generate scenarios for day-ahead markets. Our results show that the generated scenarios based on clustered wind sites outperform existing approaches in terms of reliability and sharpness and can reduce the total computational time for scenario generation and reduction significantly. The clustering-based framework can therefore provide a better support for real-world market simulations with high wind penetration.
data visualization↗
Indium tin oxide-free transparent and conductive electrode based on SnO{sub x} | Ag | SnO{sub x} for organic solar cells
A SnO{sub x} | Ag | SnO{sub x} multilayer deposited by E-beam evaporation is proposed as transparent anode for a (poly-3-hexylthiophene):[6,6]-phenyl-C{sub 61}-butyric acid methyl ester (P3HT:PCBM) bulk heterojunction based Organic Solar Cell (OSC). Such multilayers are studied and manufactured with the objective to give to the electrode its best conductivity and transparency in the visible spectral range. A transfer matrix method numerical optimization of the thicknesses of each layer of the electrode is developed to limit the number of test samples which would have been manufactured whether an empirical method was chosen. Optical characterization of the deposited SnO{sub x} and Ag thin films is performed to determine the dispersion of the complex refractive indices which are used as input parameters in the model. A satisfying agreement between numerical and experimental optical properties is found. The bare tri-layer electrodes show low sheet resistance (as low as 6.7 Ω/□) and the whole Glass | SnO{sub x} | Ag | SnO{sub x} structure presents a mean transparency on 400–700 nm spectral band as high as 67%. The multilayer is then numerically studied as anode for a P3HT:PCBM bulk heterojunction based OSC. Intrinsic absorption inside the sole active layer is calculated giving the possibility to perform optical optimization on the intrinsic absorption efficiency inside the active area by considering the media embedding the electrodes. An additional study using the morphology of the silver inserted between both oxide layers as input data is performed with a finite difference time domain 3D-method to improve the accordance between optical measurements and numerical results.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
SU-F-BRD-01: A Logistic Regression Model to Predict Objective Function Weights in Prostate Cancer IMRT
Purpose: To develop a statistical model that predicts optimization objective function weights from patient geometry for intensity-modulation radiotherapy (IMRT) of prostate cancer. Methods: A previously developed inverse optimization method (IOM) is applied retrospectively to determine optimal weights for 51 treated patients. We use an overlap volume ratio (OVR) of bladder and rectum for different PTV expansions in order to quantify patient geometry in explanatory variables. Using the optimal weights as ground truth, we develop and train a logistic regression (LR) model to predict the rectum weight and thus the bladder weight. Post hoc, we fix the weights of the left femoral head, right femoral head, and an artificial structure that encourages conformity to the population average while normalizing the bladder and rectum weights accordingly. The population average of objective function weights is used for comparison. Results: The OVR at 0.7cm was found to be the most predictive of the rectum weights. The LR model performance is statistically significant when compared to the population average over a range of clinical metrics including bladder/rectum V53Gy, bladder/rectum V70Gy, and mean voxel dose to the bladder, rectum, CTV, and PTV. On average, the LR model predicted bladder and rectum weights that are both 63% closer to the optimal weights compared to the population average. The treatment plans resulting from the LR weights have, on average, a rectum V70Gy that is 35% closer to the clinical plan and a bladder V70Gy that is 43% closer. Similar results are seen for bladder V54Gy and rectum V54Gy. Conclusion: Statistical modelling from patient anatomy can be used to determine objective function weights in IMRT for prostate cancer. Our method allows the treatment planners to begin the personalization process from an informed starting point, which may lead to more consistent clinical plans and reduce overall planning time.
60 APPLIED LIFE SCIENCES↗
A method to calibrate measurement instruments to optimize the spectrometer optics for experiment E94-107 at JLab
A method to calibrate measurement instruments through the fulfillment of physical laws is described. This method is particularly well suited to determine and/or improve magnetic spectrometer optics databases as well as to establish the best resolution achievable with them. Here, this method was applied to obtain the best resolution achievable in the excitation and binding energy spectra of several hypernuclei produced in the experiment E94-107 performed at JLab, allowing us to obtain sub-MeV resolutions.
47 OTHER INSTRUMENTATION↗
Impact of SPECT corrections on 3D-dosimetry for liver transarterial radioembolization using the patient relative calibration methodology
Purpose: Many centers aim to plan liver transarterial radioembolization (TARE) with dosimetry, even without CT-based attenuation correction (AC), or with unoptimized scatter correction (SC) methods. This work investigates the impact of presence vs absence of such corrections, and limited spatial resolution, on 3D dosimetry for TARE. Methods: Three voxelized phantoms were derived from CT images of real patients with different body sizes. Simulations of {sup 99m}Tc-SPECT projections were performed with the SIMIND code, assuming three activity distributions in the liver: uniform, inside a “liver’s segment,” or distributing multiple uptaking nodules (“nonuniform liver”), with a tumoral liver/healthy parenchyma ratio of 5:1. Projection data were reconstructed by a commercial workstation, with OSEM protocol not specifically optimized for dosimetry (spatial resolution of 12.6 mm), with/without SC (optimized, or with parameters predefined by the manufacturer; dual energy window), and with/without AC. Activity in voxels was calculated by a relative calibration, assuming identical microspheres and {sup 99m}Tc-SPECT counts spatial distribution. 3D dose distributions were calculated by convolution with {sup 90}Y voxel S-values, assuming permanent trapping of microspheres. Cumulative dose-volume histograms in lesions and healthy parenchyma from different reconstructions were compared with those obtained from the reference biodistribution (the “gold standard,” GS), assessing differences for D95%, D70%, and D50% (i.e., minimum value of the absorbed dose to a percentage of the irradiated volume). γ tool analysis with tolerance of 3%/13 mm was used to evaluate the agreement between GS and simulated cases. The influence of deep-breathing was studied, blurring the reference biodistributions with a 3D anisotropic gaussian kernel, and performing the simulations once again. Results: Differences of the dosimetric indicators were noticeable in some cases, always negative for lesions and distributed around zero for parenchyma. Application of AC and SC reduced systematically the differences for lesions by 5%–14% for a liver segment, and by 7%–12% for a nonuniform liver. For parenchyma, the data trend was less clear, but the overall range of variability passed from −10%/40% for a liver segment, and −10%/20% for a nonuniform liver, to −13%/6% in both cases. Applying AC, SC with preset parameters gave similar results to optimized SC, as confirmed by γ tool analysis. Moreover, γ analysis confirmed that solely AC and SC are not sufficient to obtain accurate 3D dose distribution. With breathing, the accuracy worsened severely for all dosimetric indicators, above all for lesions: with AC and optimized SC, −38%/−13% in liver’s segment, −61%/−40% in the nonuniform liver. For parenchyma, D50% resulted always less sensitive to breathing and sub-optimal correction methods (difference overall range: −7%/13%). Conclusions: Reconstruction protocol optimization, AC, SC, PVE and respiratory motion corrections should be implemented to obtain the best possible dosimetric accuracy. On the other side, thanks to the relative calibration, D50% inaccuracy for the healthy parenchyma from absence of AC was less than expected, while the optimization of SC was scarcely influent. The relative calibration therefore allows to perform TARE planning, basing on D50% for the healthy parenchyma, even without AC or with suboptimal corrections, rather than rely on nondosimetric methods.
60 APPLIED LIFE SCIENCES↗
Robust measurement of microbial reduction of graphene oxide nanoparticles using image analysis
ABSTRACT Shewanella oneidensis ( S. oneidensis ) has the capacity to reduce electron acceptors within a medium and is thus used frequently in microbial fuel generation, pollutant breakdown, and nanoparticle fabrication. Microbial fuel setups, however, often require costly or labor-intensive components, thus making optimization of their performance onerous. For rapid optimization of setup conditions, a model reduction assay can be employed to allow simultaneous, large-scale experiments at lower cost and effort. Since S. oneidensis uses different extracellular electron transfer pathways depending on the electron acceptor, it is essential to use a reduction assay that mirrors the pathways employed in the microbial fuel system. For microbial fuel setups that use nanoparticles to stimulate electron transfer, reduction of graphene oxide provides a more accurate model than other commonly used assays as it is a bulk material that forms flocculates in solutions with a large ionic component. However, graphene oxide flocculates can interfere with traditional absorbance-based measurement techniques. This study introduces a novel image analysis method for quantifying graphene oxide reduction, showing improved performance and statistical accuracy over traditional methods. A comparative analysis shows that the image analysis method produces smaller errors between replicates and reveals more statistically significant differences between samples than traditional plate reader measurements under conditions causing graphene oxide flocculation. Image analysis can also detect reduction activity at earlier time points due to its use of larger solution volumes, enhancing color detection. These improvements in accuracy make image analysis a promising method for optimizing microbial fuel cells that use nanoparticles or bulk substrates. IMPORTANCE Shewanella oneidensis ( S. oneidensis ) is widely used in reduction processes such as microbial fuel generation due to its capacity to reduce electron acceptors. Often, these setups are labor-intensive to operate and require days to produce results, so use of a model assay would reduce the time and expenses needed for optimization. Our research developed a novel digital analysis method for analysis of graphene oxide flocculates that may be utilized as a model assay for reduction platforms featuring nanoparticles. Use of this model reduction assay will enable rapid optimization and drive improvements in the microbial fuel generation sector.
Bennett, Danielle T. (ORCID:0009000188748827)↗
Efficient kinetic thermal inverse modeling for organic material decomposition
The prevalent use of organic materials in manufacturing is a fire safety concern, and motivates the need for predictive thermal decomposition models. A critical component of predictive modeling is numerical inference of kinetic parameters from bench scale data. Currently, an active area of computational pyrolysis research focuses on identifying efficient, robust methods for optimization. This paper demonstrates that kinetic parameter calibration problems can successfully be solved using classical gradient-based optimization. We explore calibration examples that exhibit characteristics of concern: high nonlinearity, high dimensionality, complicated schemes, overlapping reactions, noisy data, and poor initial guesses. The examples demonstrate that a simple, non-invasive change to the problem formulation can simultaneously avoid local minima, avoid computation of derivative matrices, achieve a computational efficiency speedup of 10x, and make optimization robust to perturbations of parameter components. Techniques from the mathematical optimization and inverse problem communities are employed. By re-examining gradient-based algorithms, we highlight opportunities to develop kinetic parameter calibration methods that should outperform current methods.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Evaluation of automated stability testing in machining through closed-loop control and Bayesian machine learning
Here, this paper describes a system for automated identification of the optimal stable cutting parameters in milling through Bayesian machine learning and closed-loop control. The closed-loop control system consists of a process monitoring architecture, an analysis framework, and a feedback mechanism. The analysis framework consists of a Bayesian machine learning algorithm that learns a stability map given test results. The learned stability map is used to select parameters for stability testing using an expected improvement in the material removal rate criterion. The test parameters are communicated to the machine controller to complete the test cut through a feedback mechanism. The test cuts were monitored using an audio signal; the stability of the test cut was determined by analyzing the frequency content of the audio signal. The test result was fed back to the Bayesian learning algorithm to complete the loop. Experimental results demonstrate that the system can identify the optimal stable parameters without information about the cutting force model or the structural dynamics. The system provides a low-cost method for optimal stable parameter identification in an industrial environment.
Chatter↗
Performance optimization of a bendable parabolic cylinder collimating X-ray mirror for the ALS micro-XAS beamline 10.3.2
The Advanced Light Source (ALS) beamline (BL) 10.3.2 is an apparatus for X-ray microprobe spectroscopy and diffraction experiments, operating in the energy range 2.4–17 keV. The performance of the beamline, namely the spatial and energy resolutions of the measurements, depends significantly on the collimation quality of light incident on the monochromator. In the BL 10.3.2 end-station, the synchrotron source is imaged 1:1 onto a set of roll slits which form a virtual source. The light from this source is collimated in the vertical direction by a bendable parabolic cylinder mirror. Details are presented of the mirror design, which allows for precision assembly, alignment and shaping of the mirror, as well as for extending of the mirror operating lifetime by a factor of ~10. Assembly, mirror optimal shaping and preliminary alignment were performed ex situ in the ALS X-ray Optics Laboratory (XROL). Using an original method for optimal ex situ characterization and setting of bendable X-ray optics developed at the XROL, a root-mean-square (RMS) residual surface slope error of 0.31 µrad with respect to the desired parabola, and an RMS residual height error of less than 3 nm were achieved. Once in place at the beamline, deviations from the designed optical geometry ( e.g. due to the tolerances for setting the distance to the virtual source, the grazing incidence angle, the transverse position) and/or mirror shape ( e.g. due to a heat load deformation) may appear. Due to the errors, on installation the energy spread from the monochromator is typically a few electron-volts. Here, a new technique developed and successfully implemented for at-wavelength ( in situ ) fine optimal tuning of the mirror, enabling us to reduce the collimation-induced energy spread to ~0.05 eV, is described.
43 PARTICLE ACCELERATORS↗
SU-E-T-53: Benchmarking a Monte Carlo Model for Patient Plane Leakage Calculations of Low Energy 6MV Unique Linacs
Purpose: To validate the physics parameters of a Monte Carlo model for patient plane leakage calculations on the 6MV Unique linac by comparing the simulations against IEC patient plane leakage measurements. The benchmarked model can further be used for shielding design optimization, to predict leakage in the proximity of intended treatment fields, reduce the system weight and cost, and improve components reliability. Methods: The treatment head geometry of the Unique linac was simulated in Geant4 (v9.4.p02 with “Opt3” standard electromagnetic physics list) based on CAD drawings of all collimation and shielding components projected from the target to the area within 2m from isocenter. A 4×4m2 scorer was inserted 1m from the target in the patient plane and multiple phase space files were recorded by performing a 40-node computing cluster simulation on the EC2 cloud. The photon energy fluence was calculated relative to the value at isocenter for a 10×10cm2 field using 10×10mm2 bins. Tungsten blocks were parked accordingly to represent MLC120. The secondary particle contamination to patient plane was eliminated by “killing” those particles prior to the primary collimator entrance using a “kill-plane”, which represented the upper head shielding components not being modeled. Both IEC patient-plane leakage and X/Y-jaws transmission were simulated. Results: The contribution of photons to energy fluence was 0.064% on average, in excellent agreement with the experimental data available at 0.5, 1.0, and 1.5m from isocenter, characterized by an average leakage of 0.045% and a maximum leakage of 0.085%. X- and Y-jaws transmissions of 0.43% and 0.44% were found in good agreement with measurements of 0.48% and 0.43%, respectively. Conclusion: A Geant4 model based on energy fluence calculations for the 6MV Unique linac was created and validated using IEC patient plane leakage measurements. The “kill-plane” has effectively eliminated electron contamination to patient plane in these simulations.
60 APPLIED LIFE SCIENCES↗
Optimized blind gamma-ray pulsar searches at fixed computing budget
The sensitivity of blind gamma-ray pulsar searches in multiple years worth of photon data, as from the Fermi LAT, is primarily limited by the finite computational resources available. Addressing this 'needle in a haystack' problem, here we present methods for optimizing blind searches to achieve the highest sensitivity at fixed computing cost. For both coherent and semicoherent methods, we consider their statistical properties and study their search sensitivity under computational constraints. The results validate a multistage strategy, where the first stage scans the entire parameter space using an efficient semicoherent method and promising candidates are then refined through a fully coherent analysis. We also find that for the first stage of a blind search incoherent harmonic summing of powers is not worthwhile at fixed computing cost for typical gamma-ray pulsars. Further enhancing sensitivity, we present efficiency-improved interpolation techniques for the semicoherent search stage. Via realistic simulations we demonstrate that overall these optimizations can significantly lower the minimum detectable pulsed fraction by almost 50% at the same computational expense.
79 ASTRONOMY AND ASTROPHYSICS↗
System and method for leveraging human physiological traits to control microprocessor frequency
A system and method for leveraging physiological traits to control microprocessor frequency are disclosed. In some embodiments, the system and method may optimize, for example, a particular processor-based architecture based on, for example, end user satisfaction. In some embodiments, the system and method may determine, for example, whether their users are satisfied to provide higher efficiency, improved reliability, reduced power consumption, increased security, and a better user experience. The system and method may use, for example, biometric input devices to provide information about a user's physiological traits to a computer system. Biometric input devices may include, for example, one or more of the following: an eye tracker, a galvanic skin response sensor, and/or a force sensor.
97 MATHEMATICS AND COMPUTING↗
Focus optimization at relativistic intensity with high numerical aperture and adaptive optics
Improved focusing of laser beams using high numerical aperture systems is an efficient route to increasing intensities in the ultrafast regime to relativistic levels. We experimentally demonstrate a new method of optimizing the focus of a high-power laser, using second harmonic generation at full intensity in a low-pressure gas to provide a figure of merit for optimizing the shape of a deformable mirror via a genetic algorithm. Nonlinear and thermal aberrations are corrected, and aberrations introduced by filters are avoided. Furthermore, the method is applied to focus a millijoule, short pulse (30 fs), high repetition rate laser system to relativistic intensity in both near IR and mid IR regimes.
Lin, Jinpu↗
Systematic Layout Planning of a Radiology Reporting Area to Optimize Radiologists’ Performance
Optimizing radiologists’ performance is a major priority for managers of health services/systems, since the radiologists’ reporting activity imposes a severe constraint on radiology productivity. Despite that, methods to optimize radiologists’ reporting workplace layout are scarce in the literature. This study was performed in the Radiology Division (RD) of an 850-bed University-based general hospital. The analysis of the reporting workplace layout was carried out using the systematic layout planning (SLP) method, in association with cluster analysis as a complementary tool in early stages of SLP. Radiologists, architects, and hospital managers were the stakeholders consulted for the completion of different stages of the layout planning process. A step-by-step description of the proposed methodology to plan an RD reporting layout is presented. Clusters of radiologists were defined using types of exams reported and their frequency of occurrence as clustering variables. Sectors with high degree of interaction were placed in proximity in the new RD layout, with separation of noisy and quiet areas. Four reporting cells were positioned in the quiet area, grouping radiologists by subspecialty, as follows: cluster 1-abdomen; cluster 2-musculoskeletal; cluster 3-neurological, vascular and head & neck; cluster 4-thoracic and cardiac. The creation of reporting cells has the potential to limit unplanned interruptions and enhance the exchange of knowledge and information within cells, joining radiologists with the same expertise. That should lead to improvements in productivity, allowing managers to more easily monitor radiologists’ performance.
62 RADIOLOGY AND NUCLEAR MEDICINE↗
Simulating and Optimizing Quantum State Transport
The goal of this project was to produce an accurate simulator of the “pitch and catch” process of sending quantum states between SRF cavities, and to find a method for optimizing the control pumps. We developed a program in C++ to integrate the equations of motion with high speed and precision, and used this as a basis for finding an optimal control function to maximize the state transfer efficiency. To demonstrate this we have shown an example of an optimal drive function and the resulting system dynamics, as well as a heat map of the cost function for a range of drive amplitudes.
Weston, Jacob↗
Time-Varying Feedback Optimization for Quadratic Programs with Heterogeneous Gradient Step Sizes
Online feedback-based optimization has become a promising framework for real-time optimization and control of complex engineering systems. This tutorial paper surveys the recent advances in the field as well as provides novel convergence results for primal-dual online algorithms with heterogeneous step sizes for different elements of the gradient. The analysis is performed for quadratic programs and the approach is illustrated on applications for adaptive step-size and model-free online algorithms, in the context of optimal control of modern power systems.
gradient methods↗