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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.

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At least 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2015

TU-EF-304-03: 4D Monte Carlo Robustness Test for Proton Therapy

Purpose: Breathing motion and approximate dose calculation engines may increase proton range uncertainties. We address these two issues using a comprehensive 4D robustness evaluation tool based on an efficient Monte Carlo (MC) engine, which can simulate breathing with no significant increase in computation time. Methods: To assess the robustness of the treatment plan, multiple scenarios of uncertainties are simulated, taking into account the systematic and random setup errors, range uncertainties, and organ motion. Our fast MC dose engine, called MCsquare, implements optimized models on a massively-parallel computation architecture and allows us to accurately simulate a scenario in less than one minute. The deviations of the uncertainty scenarios are then reported on a DVH-band and compared to the nominal plan.The robustness evaluation tool is illustrated in a lung case by comparing three 60Gy treatment plans. First, a plan is optimized on a PTV obtained by extending the CTV with an 8mm margin, in order to take into account systematic geometrical uncertainties, like in our current practice in radiotherapy. No specific strategy is employed to correct for tumor and organ motions. The second plan involves a PTV generated from the ITV, which encompasses the tumor volume in all breathing phases. The last plan results from robust optimization performed on the ITV, with robustness parameters of 3% for tissue density and 8 mm for positioning errors. Results: The robustness test revealed that the first two plans could not properly cover the target in the presence of uncertainties. CTV-coverage (D95) in the three plans ranged respectively between 39.4–55.5Gy, 50.2–57.5Gy, and 55.1–58.6Gy. Conclusion: A realistic robustness verification tool based on a fast MC dose engine has been developed. This test is essential to assess the quality of proton therapy plan and very useful to study various planning strategies for mobile tumors. This work is partly funded by IBA (Louvain-la-Neuve, Belgium)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

SU-F-R-31: Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease

Purpose: Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (radiation pneumonitis and radiation fibrosis). For these features to be clinically useful, they need to be relatively invariant (robust) to tumor size and not correlated with normal lung volume. Methods: The free-breathing CTs of 14 lung SBRT patients were studied. Different sizes of GTVs were simulated with spheres placed at the upper lobe and lower lobe respectively in the normal lung (contralateral to tumor). 27 texture features (9 from intensity histogram, 8 from grey-level co-occurrence matrix [GLCM] and 10 from grey-level run-length matrix [GLRM]) were extracted from [normal lung-GTV]. To measure the variability of a feature F, the relative difference D=|Fref -Fsim|/Fref*100% was calculated, where Fref was for the entire normal lung and Fsim was for [normal lung-GTV]. A feature was considered as robust if the largest non-outlier (Q3+1.5*IQR) D was less than 5%, and considered as not correlated with normal lung volume when their Pearson correlation was lower than 0.50. Results: Only 11 features were robust. All first-order intensity-histogram features (mean, max, etc.) were robust, while most higher-order features (skewness, kurtosis, etc.) were unrobust. Only two of the GLCM and four of the GLRM features were robust. Larger GTV resulted greater feature variation, this was particularly true for unrobust features. All robust features were not correlated with normal lung volume while three unrobust features showed high correlation. Excessive variations were observed in two low grey-level run features and were later identified to be from one patient with local lung diseases (atelectasis) in the normal lung. There was no dependence on GTV location. Conclusion: We identified 11 robust normal lung CT texture features that can be further examined for the prediction of radiation-induced lung disease. Interestingly, low grey-level run features identified normal lung diseases. This work was supported in part by the National Cancer Institute Grants R01CA172638.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TH-CD-209-04: Fuzzy Robust Optimization in Intensity-Modulated Proton Therapy Planning to Account for Range and Patient Setup Uncertainties

Purpose: We propose to apply a robust optimization model based on fuzzy-logic constraints in the intensity-modulated proton therapy (IMPT) planning subject to range and patient setup uncertainties. The purpose is to ensure the plan robustness under uncertainty and obtain the best trade-off between tumor dose coverage and organ-at-risk(OAR) sparing. Methods: Two IMPT plans were generated for 3 head-and-neck cancer patients: one used the planning target volume(PTV) method; the other used the fuzzy robust optimization method. In the latter method, nine dose distributions were computed - the nominal one and one each for ±3mm setup uncertainties along three cardinal axes and for ±3.5% range uncertainty. For tumors, these nine dose distributions were explicitly controlled by adding hard constraints with adjustable parameters. For OARs, fuzzy constraints that allow the dose to vary within a certain range were used so that the tumor dose distribution was guaranteed by minimum compromise of that of OARs. We rendered this model tractable by converting the fuzzy constraints to linear constraints. The plan quality was evaluated using dose-volume histogram(DVH) indices such as tumor dose coverage(D95%), homogeneity(D5%-D95%), plan robustness(DVH band at D95%), and OAR sparing like D1% of brain and D1% of brainstem. Results: Our model could yield clinically acceptable plans. The fuzzy-logic robust optimization method produced IMPT plans with comparable target dose coverage and homogeneity compared to the PTV method(unit: Gy[RBE]; average[min, max])(CTV D95%: 59 [52.7, 63.5] vs 53.5[46.4, 60.1], CTV D5% - D95%: 11.1[5.3, 18.6] vs 14.4[9.2, 21.5]). It also generated more robust plans(CTV DVH band at D95%: 3.8[1.2, 5.6] vs 11.5[6.2, 16.7]). The parameters of tumor constraints could be adjusted to control the tradeoff between tumor coverage and OAR sparing. Conclusion: The fuzzy-logic robust optimization generates superior IMPT with minimum compromise of OAR sparing. This research was supported by the National Cancer Institute Career Developmental Award K25CA168984, by the Fraternal Order of Eagles Cancer Research Fund Career Development Award, by The Lawrence W. and Marilyn W. Matteson Fund for Cancer Research, by Mayo Arizona State University Seed Grant, and by The Kemper Marley Foundation. eRA Person ID(s) for the Principal Investigator: 11017970 (Research Supported by National Institutes of Health)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2013

Dual Regulation of Gene Expression Mediated by Extended MAPK Activation and Salicylic Acid Contributes to Robust Innate Immunity in Arabidopsis thaliana

Network robustness is a crucial property of the plant immune signaling network because pathogens are under a strong selection pressure to perturb plant network components to dampen plant immune responses. Nevertheless, modulation of network robustness is an area of network biology that has rarely been explored. While two modes of plant immunity, Effector-Triggered Immunity (ETI) and Pattern-Triggered Immunity (PTI), extensively share signaling machinery, the network output is much more robust against perturbations during ETI than PTI, suggesting modulation of network robustness. Here, we report a molecular mechanism underlying the modulation of the network robustness in Arabidopsis thaliana. The salicylic acid (SA) signaling sector regulates a major portion of the plant immune response and is important in immunity against biotrophic and hemibiotrophic pathogens. In Arabidopsis, SA signaling was required for the proper regulation of the vast majority of SA-responsive genes during PTI. However, during ETI, regulation of most SA-responsive genes, including the canonical SA marker gene PR1, could be controlled by SA-independent mechanisms as well as by SA. The activation of the two immune-related MAPKs, MPK3 and MPK6, persisted for several hours during ETI but less than one hour during PTI. Sustained MAPK activation was sufficient to confer SA-independent regulation of most SA-responsive genes. Furthermore, the MPK3 and SA signaling sectors were compensatory to each other for inhibition of bacterial growth as well as for PR1 expression during ETI. These results indicate that the duration of the MAPK activation is a critical determinant for modulation of robustness of the immune signaling network. Our findings with the plant immune signaling network imply that the robustness level of a biological network can be modulated by the activities of network components.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS1981

Practical robustness measures in multivariable control system analysis

The robustness of the stability of multivariable linear time invariant feedback control systems with respect to model uncertainty is considered using frequency domain criteria. Available robustness tests are unified under a common framework based on the nature and structure of model errors. These results are derived using a multivariable version of Nyquist's stability theorem in which the minimum singular value of the return difference transfer matrix is shown to be the multivariable generalization of the distance to the critical point on a single input, single output Nyquist diagram. Using the return difference transfer matrix, a very general robustness theorem is presented from which all of the robustness tests dealing with specific model errors may be derived. The robustness tests that explicitly utilized model error structure are able to guarantee feedback system stability in the face of model errors of larger magnitude than those robustness tests that do not. The robustness of linear quadratic Gaussian control systems are analyzed.

Lehtomaki, N. A.↗
NASA NTRS1981

Robustness tests utilizing the structure of modelling error

The present investigation is essentially concerned with the extension of results presented by Lehtomaki et al. (1981) on the robustness of multivariable linear time invariant feedback control systems. The work reported by Lehtomaki et al. is based on a multivariable version of Nyquist's theorem from which several robustness theorems were derived. In connection with the current investigation a slightly more general approach based on Nyquist's theorem is given in a fundamental robustness theorem from which various robustness tests may be obtained. A fundamental characterization of robustness is considered, and important tools from matrix theory are introduced. Attention is given to robustness tests and unstructured model error, and a robustness analysis for linear systems with structured model error.

Lehtomaki, N. A.↗
NASA NTRS1990

Stochastic performance robustness of aircraft control systems

Stochastic robustness, a simple technique used to estimate the robustness of linear, time-invariant systems, is applied to a twin-jet transport aircraft control system. Concepts behind stochastic stability robustness are extended to stochastic performance robustness. Stochastic performance robustness measures based on classical design specifications and measures specific to aircraft handling qualities are introduced. Confidence intervals for both individual stochastic robustness measures and for comparing two measures are presented. The application of stochastic performance robustness, the use of confidence intervals, and tradeoffs between performance objectives are demonstrated by means of the twin-jet aircraft example.

Stengel, Robert F.↗
NASA NTRS1990

Design optimization for cost and quality: The robust design approach

Designing reliable, low cost, and operable space systems has become the key to future space operations. Designing high quality space systems at low cost is an economic and technological challenge to the designer. A systematic and efficient way to meet this challenge is a new method of design optimization for performance, quality, and cost, called Robust Design. Robust Design is an approach for design optimization. It consists of: making system performance insensitive to material and subsystem variation, thus allowing the use of less costly materials and components; making designs less sensitive to the variations in the operating environment, thus improving reliability and reducing operating costs; and using a new structured development process so that engineering time is used most productively. The objective in Robust Design is to select the best combination of controllable design parameters so that the system is most robust to uncontrollable noise factors. The robust design methodology uses a mathematical tool called an orthogonal array, from design of experiments theory, to study a large number of decision variables with a significantly small number of experiments. Robust design also uses a statistical measure of performance, called a signal-to-noise ratio, from electrical control theory, to evaluate the level of performance and the effect of noise factors. The purpose is to investigate the Robust Design methodology for improving quality and cost, demonstrate its application by the use of an example, and suggest its use as an integral part of space system design process.

Unal, Resit↗
NASA NTRS1991

Robust control of systems with real parameter uncertainty and unmodelled dynamics

During this research period we have made significant progress in the four proposed areas: (1) design of robust controllers via H infinity optimization; (2) design of robust controllers via mixed H2/H infinity optimization; (3) M-delta structure and robust stability analysis for structured uncertainties; and (4) a study on controllability and observability of perturbed plant. It is well known now that the two-Riccati-equation solution to the H infinity control problem can be used to characterize all possible stabilizing optimal or suboptimal H infinity controllers if the optimal H infinity norm or gamma, an upper bound of a suboptimal H infinity norm, is given. In this research, we discovered some useful properties of these H infinity Riccati solutions. Among them, the most prominent one is that the spectral radius of the product of these two Riccati solutions is a continuous, nonincreasing, convex function of gamma in the domain of interest. Based on these properties, quadratically convergent algorithms are developed to compute the optimal H infinity norm. We also set up a detailed procedure for applying the H infinity theory to robust control systems design. The desire to design controllers with H infinity robustness but H(exp 2) performance has recently resulted in mixed H(exp 2) and H infinity control problem formulation. The mixed H(exp 2)/H infinity problem have drawn the attention of many investigators. However, solution is only available for special cases of this problem. We formulated a relatively realistic control problem with H(exp 2) performance index and H infinity robustness constraint into a more general mixed H(exp 2)/H infinity problem. No optimal solution yet is available for this more general mixed H(exp 2)/H infinity problem. Although the optimal solution for this mixed H(exp 2)/H infinity control has not yet been found, we proposed a design approach which can be used through proper choice of the available design parameters to influence both robustness and performance. For a large class of linear time-invariant systems with real parametric perturbations, the coefficient vector of the characteristic polynomial is a multilinear function of the real parameter vector. Based on this multilinear mapping relationship together with the recent developments for polytopic polynomials and parameter domain partition technique, we proposed an iterative algorithm for coupling the real structured singular value.

Chang, Bor-Chin↗
NASA NTRS1993

A Monte Carlo approach to the analysis of control system robustness

Stochastic robustness, a simple technique used to estimate the stability and performance robustness of linear, time-invariant systems, is described. The scalar probability of instability is introduced as a measure of stability robustness. Examples are given of stochastic performance robustness measures based on classical time-domain specifications. The relationship between stochastic robustness measures and control system design parameters is discussed. The technique is demonstrated by analyzing an LQG/LTR system designed for a flexible robot arm. It is concluded that the analysis of stochastic robustness offers a good alternative to existing robustness metrics.

Ray, Laura R.↗
DOE OSTI2020

Robust foil regenerator flow loss and heat transfer tests under oscillating flow condition

A regenerator works as an energy storage component in a Stirling engine. Thus, it is one of the most critical components that makes the Stirling engine highly efficient. Traditionally, the regenerators are made of wire media such as woven screens and random fibers. These wire regenerators experience considerably high flow losses through the regenerator due to the flow separation and the resulting vortices. The high flow losses associated with the flow separation and vortices result in a lower engine efficiency. This research is to test a new robust foil regenerator to investigate its feasibility for free-piston Stirling engine applications. The robust foil regenerator is configured with parallel flow channels and stiffening ribs. Comparing to complex flows patterns in woven screen and random fiber regenerators, the flows in the parallel plates are simple and the flow losses are considerably small, and the heat transfer coefficient is also relatively small. To test the regenerator experimentally, a regenerator test rig was manufactured. To verify the accuracy of the test rig, a woven screen regenerator was made and tested prior to the robust foil regenerator test. The friction factor correlation of the woven screen regenerator shows a good agreement with the published regenerator correlations. The robust foil regenerator tests were conducted under the oscillating flow condition with different Reynolds numbers. The flow losses were measured with dynamic pressure transducers and the friction coefficient was derived from measured pressure drop. The measured temperature difference over the regenerator was used to calculate the heat transfer coefficient and Nusselt number. The figure of merit with two methods of NPH/NTU ratio and j/f ratio was calculated to evaluate the suitability of the robust foil regenerator. The results show that the robust foil regenerator has considerably higher figure of merit and therefore, better performance than other types of regenerator.

42 ENGINEERING↗
DOE OSTI2018

Robust Operation of Soft Open Points in Active Distribution Networks with High Penetration of Photovoltaic Integration

Distributed generators (DGs) including photovoltaic panels (PVs) have been integrated dramatically in active distribution networks (ADNs). Due to the strong volatility and uncertainty, the high penetration of PV generation immensely exacerbates the conditions of voltage violation in ADNs. However, the emerging flexible interconnection technology based on soft open points (SOPs) provides increased controllability and flexibility to the system operation. For fully exploiting the regulation ability of SOPs to address the problems caused by PV, this paper proposes a robust optimization method to achieve the robust optimal operation of SOPs in ADNs. A two-stage adjustable robust optimization model is built to tackle the uncertainties of PV outputs, in which robust operation strategies of SOPs are generated to eliminate the voltage violations and reduce the power losses of ADNs. A column-and-constraint generation (C&CG) algorithm is developed to solve the proposed robust optimization model, which are formulated as second-order cone program (SOCP) to facilitate the accuracy and computation efficiency. Here, case studies on the modified IEEE 33-node system and comparisons with the deterministic optimization approach are conducted to verify the effectiveness and robustness of the proposed method.

14 SOLAR ENERGY↗
DOE OSTI2023

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks. In particular, the eye is a signature feature of a mature TC. Therefore, knowing the eyes’ locations and movements is crucial for both operational weather forecasts and climate risk assessments. Recently, a multilevel robustness framework has been introduced to study the critical points of time-varying vector fields. The framework quantifies the robustness (i.e., structural stability) of critical points across varying neighborhoods. By relating the multilevel robustness with critical point tracking, the framework has demonstrated its potential in cyclone tracking. An advantage is that it identifies cyclonic features using only 2D wind vector fields, which is encouraging as most tracking algorithms require multiple dynamic and thermodynamic variables at different altitudes. A disadvantage is that the framework does not scale well computationally for datasets containing a large number of cyclones. Herein this paper introduces a topologically robust physics-informed tracking framework (TROPHY) for TC tracking. The main idea is to integrate physical knowledge of TC to drastically improve the computational efficiency of multilevel robustness framework for large-scale climate datasets. First, during preprocessing, we propose a physics-informed feature selection strategy to filter 90% of critical points that are short-lived and have low stability, thus preserving good candidates for TC tracking. Second, during in-processing, we impose constraints during the multilevel robustness computation to focus only on physics-informed neighborhoods of TCs. We apply TROPHY to 30 years of 2D wind fields from reanalysis data in ERA5 and generate a number of TC tracks. In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics (e.g., frequency, intensity, duration, latitudes with maximum intensity, and genesis) that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Quantifying the robustness of deep multispectral segmentation models against natural perturbations and data poisoning

In overhead image segmentation tasks, including additional spectral bands beyond the traditional RGB channels can improve model performance. However, it is still unclear how incorporating this additional data impacts model robustness to adversarial attacks and natural perturbations. For adversarial robustness, the additional in-formation could improve the model’s ability to distinguish malicious inputs, or simply provide new attack avenues and vulnerabilities. For natural perturbations, the additional information could better inform model decisions and weaken perturbation effects or have no significant influence at all. In this work, we seek to characterize the performance and robustness of a multispectral (RGB and near infrared) image segmentation model subjected to adversarial attacks and natural perturbations. While existing adversarial and natural robustness research has focused primarily on digital perturbations, we prioritize on creating realistic perturbations designed with physical world conditions in mind. For adversarial robustness, we focus on data poisoning attacks whereas for natural robustness, we focus on extending ImageNet-C common corruptions for fog and snow that coherently and self-consistently perturbs the input data. Overall, we find both RGB and multispectral models are vulnerable to data poisoning attacks regardless of input or fusion architectures and that while physically-realizable natural perturbations still degrade model performance, the impact differs based on fusion architecture and input data.

Deep learning, multispectral images, multimodal fu↗
DOE OSTI2019

A metric for evaluating conformance robustness during geologic CO 2 sequestration operations

A metric for quantifying the robustness of a designation of conformance of a geologic CO 2 sequestration (GCS) project during its operational phase is developed and demonstrated. Conformance in this context is a measure of the degree to which the sequestration system is understood and can be accurately modeled along with the degree to which the storage system is performing as designed. The robustness of conformance quantifies the degree to which parameter values can deviate from their current nominal estimates and still produce model forecasts that meet the performance criteria for the GCS operation. We develop and demonstrate the approach on a simplified scenario to illustrate the concept using a single uncertain parameter (homogeneous reservoir permeability) and a single performance criterion (critical pressure at a monitoring well in the reservoir; i.e., one that may displace brine from the reservoir to an overlying drinking water aquifer for example). Increased confidence in conformance assessment as more monitoring data are obtained is incorporated through the standard error of the coefficient (reservoir permeability in the case presented here), which we designate as the concordance metric. As more monitoring data become available during the course of the GCS operation, the standard error of the coefficient decreases (in general), thereby leading to increased conformance robustness as a larger deviation from nominal is required to fail to meet performance criteria. Increasing conformance robustness over time builds confidence that a GCS project will continue to meet performance criteria during the life-span of the project, thereby supporting designations of conformance. Furthermore a lack of conformance robustness provides a critical warning that the performance criteria of the GCS operation are not robust against probabilistic and non-probabilistic uncertainty in model conceptualization and/or model parameters.

58 GEOSCIENCES↗
DOE OSTI2016

An Analysis of Plan Robustness for Esophageal Tumors: Comparing Volumetric Modulated Arc Therapy Plans and Spot Scanning Proton Planning

Purpose: Planning studies to compare x-ray and proton techniques and to select the most suitable technique for each patient have been hampered by the nonequivalence of several aspects of treatment planning and delivery. A fair comparison should compare similarly advanced delivery techniques from current clinical practice and also assess the robustness of each technique. The present study therefore compared volumetric modulated arc therapy (VMAT) and single-field optimization (SFO) spot scanning proton therapy plans created using a simultaneous integrated boost (SIB) for dose escalation in midesophageal cancer and analyzed the effect of setup and range uncertainties on these plans. Methods and Materials: For 21 patients, SIB plans with a physical dose prescription of 2 Gy or 2.5 Gy/fraction in 25 fractions to planning target volume (PTV){sub 50Gy} or PTV{sub 62.5Gy} (primary tumor with 0.5 cm margins) were created and evaluated for robustness to random setup errors and proton range errors. Dose–volume metrics were compared for the optimal and uncertainty plans, with P<.05 (Wilcoxon) considered significant. Results: SFO reduced the mean lung dose by 51.4% (range 35.1%-76.1%) and the mean heart dose by 40.9% (range 15.0%-57.4%) compared with VMAT. Proton plan robustness to a 3.5% range error was acceptable. For all patients, the clinical target volume D{sub 98} was 95.0% to 100.4% of the prescribed dose and gross tumor volume (GTV) D{sub 98} was 98.8% to 101%. Setup error robustness was patient anatomy dependent, and the potential minimum dose per fraction was always lower with SFO than with VMAT. The clinical target volume D{sub 98} was lower by 0.6% to 7.8% of the prescribed dose, and the GTV D{sub 98} was lower by 0.3% to 2.2% of the prescribed GTV dose. Conclusions: The SFO plans achieved significant sparing of normal tissue compared with the VMAT plans for midesophageal cancer. The target dose coverage in the SIB proton plans was less robust to random setup errors and might be unacceptable for certain patients. Robust optimization to ensure adequate target coverage of SIB proton plans might be beneficial.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2016

Robust Proton Pencil Beam Scanning Treatment Planning for Rectal Cancer Radiation Therapy

Purpose: To investigate, in a treatment plan design and robustness study, whether proton pencil beam scanning (PBS) has the potential to offer advantages, relative to interfraction uncertainties, over photon volumetric modulated arc therapy (VMAT) in a locally advanced rectal cancer patient population. Methods and Materials: Ten patients received a planning CT scan, followed by an average of 4 weekly offline CT verification CT scans, which were rigidly co-registered to the planning CT. Clinical PBS plans were generated on the planning CT, using a single-field uniform-dose technique with single-posterior and parallel-opposed (LAT) fields geometries. The VMAT plans were generated on the planning CT using 2 6-MV, 220° coplanar arcs. Clinical plans were forward-calculated on verification CTs to assess robustness relative to anatomic changes. Setup errors were assessed by forward-calculating clinical plans with a ±5-mm (left–right, anterior–posterior, superior–inferior) isocenter shift on the planning CT. Differences in clinical target volume and organ at risk dose–volume histogram (DHV) indicators between plans were tested for significance using an appropriate Wilcoxon test (P<.05). Results: Dosimetrically, PBS plans were statistically different from VMAT plans, showing greater organ at risk sparing. However, the bladder was statistically identical among LAT and VMAT plans. The clinical target volume coverage was statistically identical among all plans. The robustness test found that all DVH indicators for PBS and VMAT plans were robust, except the LAT's genitalia (V5, V35). The verification CT plans showed that all DVH indicators were robust. Conclusions: Pencil beam scanning plans were found to be as robust as VMAT plans relative to interfractional changes during treatment when posterior beam angles and appropriate range margins are used. Pencil beam scanning dosimetric gains in the bowel (V15, V20) over VMAT suggest that using PBS to treat rectal cancer may reduce radiation treatment–related toxicity.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Robustness of inertial fusion energy relevant implosions to low-mode asymmetries

Inertial confinement fusion implosions for power production need to be robust. Degradation sources need to be understood and considered for an economic power plant. In this work, the impact of low-mode asymmetries on yield is studied using 2D radiation hydrodynamics simulations for inertial fusion energy relevant implosions. First, a high-gain indirectly driven capsule design is developed. This design is subsequently degraded with low-mode drive asymmetries. The results show that yield is constant with increasing amounts of asymmetry until a cliff is reached where the yield quickly drops below ignition. Robustness arises because the degraded hotspot still has enough time to get to ignition before capsule decompression. This robustness occurs even though the asymmetry couples less energy to the hotspot and causes decompression to occur sooner. The robustness is linked to the generalized Lawson parameter, χ⁠. The value of χ steadily decreases with increasing asymmetry. Once χ is close to one, the hotspot is no longer able to ignite before the capsule decompresses. A simple piston model is used to predict where the robustness cliff is for any design. The trade-off between yield and robustness is also demonstrated.

Physics - Plasma physics↗