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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Parallel storage system with burst buffer appliance for storage of partitioned key-value store across a plurality of storage tiers

Parallel storage systems are provided with a burst buffer appliance for storage of a partitioned key-value store across a plurality of storage tiers. The burst buffer appliance is configured to store key-value data on first and second storage tiers comprising respective disjoint subsets of storage. One or more servers in the partitioned key-value store provide (i) an interface between one or more local key-value stores and one or more additional storage architectures, and/or (ii) a key value interface that provides access to at least one hardware key-value store. The local key-values are optionally sorted both locally by the local store and globally by the overall MDHIM framework. The local and global sorting can be leveraged to provide batch input/output (IO) operations that aggregate multiple requests into batch operations on one or more sorted ranges.

Bent, John M.↗
DOE OSTI2013

Reassessment of True Core Collapse Differential Pressure Values for Filter Elements in Safety Critical Environments - 13076

As the areas of application for diverse filter types increases, the mechanics and material sciences associated with the hardware and its relationship with more and more arduous process environments becomes critical to the successful and reliable operation of the filtration equipment. Where the filter is the last safe barrier between the process and the life environment, structural integrity and reliability is paramount in both the validation and the ethical acceptability of the designed equipment. Core collapse is a key factor influencing filter element selection, and is an extremely complex issue with a number of variables and failure mechanisms. It is becoming clear that the theory behind core collapse calculations is not always supported with real tested data. In exploring this issue we have found that the calculation method is not always reflective of the true as tested collapse value, with the calculated values being typically in excess or even an order of magnitude higher than the tested values. The above claim is supported by a case study performed by the author, which disproves most of what was previously understood to be true. This paper also aims to explore the various failure mechanisms of different configurations of filter core, comparing calculated collapse values against real tested values, with a view to understanding a method of calculating their true collapse value. As the technology is advancing, and filter elements are being used in higher temperature, higher pressure, more radioactive and more chemically aggressive environments, confidence in core collapse values and data is crucial. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory

Risk-sensitive reinforcement learning (RL) has garnered significant attention in recent years due to the growing interest in deploying RL agents in real-world scenarios. A critical aspect of risk awareness involves modelling highly rare risk events (rewards) that could potentially lead to catastrophic outcomes. These infrequent occurrences present a formidable challenge for data-driven methods aiming to capture such risky events accurately. While risk-aware RL techniques do exist, they suffer from high variance estimation due to the inherent data scarcity. Our work proposes to enhance the resilience of RL agents when faced with very rare and risky events by focusing on refining the predictions of the extreme values predicted by the state-action value distribution. To achieve this, we formulate the extreme values of the state-action value function distribution as parameterized distributions, drawing inspiration from the principles of extreme value theory (EVT). We propose an extreme value theory based actor-critic approach, namely, Extreme Valued Actor-Critic (EVAC) which effectively addresses the issue of infrequent occurrence by leveraging EVT-based parameterization. Importantly, we theoretically demonstrate the advantages of employing these parameterized distributions in contrast to other risk-averse algorithms. Our evaluations show that the proposed method outperforms other risk averse RL algorithms on a diverse range of benchmark tasks, each encompassing distinct risk scenarios.

Wang, Yu↗
DOE OSTI2018

A Heuristic Approach to Value-Driven Evaluation of Visualizations

Recently, an approach for determining the value of a visualization was proposed, one moving beyond simple measurements of task accuracy and speed. The value equation contains components for the time savings a visualization provides, the insights and insightful questions it spurs, the overall essence of the data it conveys, and the confidence about the data and its domain it inspires. This articulation of value is purely descriptive, however, providing no actionable method of assessing a visualization's value. In this work, we create a heuristic-based evaluation methodology to accompany the value equation for assessing interactive visualizations. We refer to the methodology colloquially as ICE-T, based on an anagram of the four value components. Our approach breaks the four components down into guidelines, each of which is made up of a small set of low-level heuristics. Evaluators who have knowledge of visualization design principles then assess the visualization with respect to the heuristics. We conducted an initial trial of the methodology on three interactive visualizations of the same data set, each evaluated by 15 visualization experts. As a result, we found that the methodology showed promise, obtaining consistent ratings across the three visualizations and mirroring judgments of the utility of the visualizations by instructors of the course in which they were developed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

The economic value of grassland species for carbon storage

Carbon storage by ecosystems is valuable for climate protection. Biodiversity conservation may help increase carbon storage, but the value of this influence has been difficult to assess. We use plant, soil, and ecosystem carbon storage data from two grassland biodiversity experiments to show that greater species richness increases economic value: Increasing species richness from 1 to 10 had twice the economic value of increasing species richness from 1 to 2. The marginal value of each additional species declined as species accumulated, reflecting the nonlinear relationship between species richness and plant biomass production. Here, our demonstration of the economic value of biodiversity for enhancing carbon storage provides a foundation for assessing the value of biodiversity for decisions about land management. Combining carbon storage with other ecosystem services affected by biodiversity may well enhance the economic arguments for conservation even further.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Tumor‐pH‐value responsive non‐peripheral substituted phthalocyanines: Synthesis, investigation of photophysical and photochemical properties

Cancer is one of the diseases with the highest mortality rate worldwide. Although PDT has recently produced encouraging outcomes, there are still many areas that need to be improved. The first of these is the negative consequences faced by patients treated with the PDT method when exposed to sunlight. For this reason, a new PDT method has been developed in recent years, and it is aimed at using photosensitizer molecules that can be active in acidic conditions. Since the pH values of tumor tissues are more acidic than normal tissues, preparing molecules that act effectively in acidic conditions will allow for more effective results in treating cancer with PDT. In this context, within the scope of this study, 3‐(4‐propionylphenoxy)phthalonitrile ( 1 ) and its non‐peripheral tetra‐substituted phthalocyanine derivatives [( 2 ), ( 3 ), and ( 4 )] were prepared. With these phthalocyanine derivatives, the novel compounds ( 5 ), ( 6 ), and ( 7 ) were synthesized for the first time. The aggregation tendencies of newly synthesized phthalocyanines ( 5–7 ) were investigated in solvent media. The effects of pH changes upon UV–Vis and fluorescence spectra were performed. The electronic and emission spectra of synthesized phthalocyanine derivatives are highly sensitive to pH changes. Formation constant (Log K) values of mono‐ and di‐protonated phthalocyanine forms were calculated by the Henderson–Hasselback equation. The mono‐ and di‐protonated species' equilibrium constants (logK 1 and logK 2 ) were calculated as ~5.0. This value may be promising for pH‐sensitizing photosensitizers. Also, the photophysical and photochemical properties of synthesized metallophthalocyanine derivatives ( 2 ) and ( 5 ) were studied at different pH values. The singlet oxygen quantum yield of ( 2 ) and ( 5 ) was calculated to be 0.78 and 0.81 in DMSO, respectively. When pH = 6.4, that is, tumor‐pH‐values, this value for ( 5 ) has increased to 0.92. The newly synthesized phthalocyanines are suitable photosensitizers for PDT applications, especially with high singlet oxygen quantum yield at pH 6.4.

Genc Bilgicli, Hayriye↗
DOE OSTI2014

Weak values and weak coupling maximizing the output of weak measurements

In a weak measurement, the average output 〈o〉 of a probe that measures an observable A{sup -hat} of a quantum system undergoing both a preparation in a state ρ{sub i} and a postselection in a state E{sub f} is, to a good approximation, a function of the weak value A{sub w}=Tr[E{sub f}A{sup -hat} ρ{sub i}]/Tr[E{sub f}ρ{sub i}], a complex number. For a fixed coupling λ, when the overlap Tr[E{sub f}ρ{sub i}] is very small, A{sub w} diverges, but 〈o〉 stays finite, often tending to zero for symmetry reasons. This paper answers the questions: what is the weak value that maximizes the output for a fixed coupling? What is the coupling that maximizes the output for a fixed weak value? We derive equations for the optimal values of A{sub w} and λ, and provide the solutions. The results are independent of the dimensionality of the system, and they apply to a probe having a Hilbert space of arbitrary dimension. Using the Schrödinger–Robertson uncertainty relation, we demonstrate that, in an important case, the amplification 〈o〉 cannot exceed the initial uncertainty σ{sub o} in the observable o{sup -hat}, we provide an upper limit for the more general case, and a strategy to obtain 〈o〉≫σ{sub o}. - Highlights: •We have provided a general framework to find the extremal values of a weak measurement. •We have derived the location of the extremal values in terms of preparation and postselection. •We have devised a maximization strategy going beyond the limit of the Schrödinger–Robertson relation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Quality Assurance With Plan Veto: Reincarnation of a Record and Verify System and Its Potential Value

Purpose: To quantify the potential impact of the Integrating the Healthcare Enterprise–Radiation Oncology Quality Assurance with Plan Veto (QAPV) on patient safety of external beam radiation therapy (RT) operations. Methods and Materials: An institutional database of events (errors and near-misses) was used to evaluate the ability of QAPV to prevent clinically observed events. We analyzed reported events that were related to Digital Imaging and Communications in Medicine RT plan parameter inconsistencies between the intended treatment (on the treatment planning system) and the delivered treatment (on the treatment machine). Critical Digital Imaging and Communications in Medicine RT plan parameters were identified. Each event was scored for importance using the Failure Mode and Effects Analysis methodology. Potential error occurrence (frequency) was derived according to the collected event data, along with the potential event severity, and the probability of detection with and without the theoretical implementation of the QAPV plan comparison check. Failure Mode and Effects Analysis Risk Priority Numbers (RPNs) with and without QAPV were compared to quantify the potential benefit of clinical implementation of QAPV. Results: The implementation of QAPV could reduce the RPN values for 15 of 22 (71%) of evaluated parameters, with an overall average reduction in RPN of 68 (range, 0-216). For the 6 high-risk parameters (>200), the average reduction in RPN value was 163 (range, 108-216). The RPN value reduction for the intermediate-risk (200 > RPN > 100) parameters was (0-140). With QAPV, the largest RPN value for “Beam Meterset” was reduced from 324 to 108. The maximum reduction in RPN value was for Beam Meterset (216, 66.7%), whereas the maximum percentage reduction was for Cumulative Meterset Weight (80, 88.9%). Conclusion: This analysis quantifies the value of the Integrating the Healthcare Enterprise–Radiation Oncology QAPV implementation in clinical workflow. We demonstrate that although QAPV does not provide a comprehensive solution for error prevention in RT, it can have a significant impact on a subset of the most severe clinically observed events.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2013

The composition, heating value and renewable share of the energy content of mixed municipal solid waste in Finland

Highlights: • New experimental data of mixed MSW properties in a Finnish case region. • The share of renewable energy of mixed MSW. • The results were compared with earlier international studies. • The average share of renewable energy was 30% and the average LHVar 19 MJ/kg. • Well operating source separation decreases the renewable energy content of MSW. - Abstract: For the estimation of greenhouse gas emissions from waste incineration it is essential to know the share of the renewable energy content of the combusted waste. The composition and heating value information is generally available, but the renewable energy share or heating values of different fractions of waste have rarely been determined. In this study, data from Finnish studies concerning the composition and energy content of mixed MSW were collected, new experimental data on the compositions, heating values and renewable share of energy were presented and the results were compared to the estimations concluded from earlier international studies. In the town of Lappeenranta in south-eastern Finland, the share of renewable energy ranged between 25% and 34% in the energy content tests implemented for two sample trucks. The heating values of the waste and fractions of plastic waste were high in the samples compared to the earlier studies in Finland. These high values were caused by good source separation and led to a low share of renewable energy content in the waste. The results showed that in mixed municipal solid waste the renewable share of the energy content can be significantly lower than the general assumptions (50–60%) when the source separation of organic waste, paper and cardboard is carried out successfully. The number of samples was however small for making extensive conclusions on the results concerning the heating values and renewable share of energy and additional research is needed for this purpose.

09 BIOMASS FUELS↗
DOE OSTI2016

ENVIRONMENTAL REVIEWS AND CASE STUDIES: The National Park Service Visual Resource Inventory: Capturing the Historic and Cultural Values of Scenic Views

Several United States (US) federal agencies have developed visual resource inventory (VRI) and management systems that reflect specific agency missions and visual resource management objectives. These programs have varied in the degree to which they incorporate historic and cultural elements and values into the scenic inventory process. The recent nationwide expansion of renewable energy and associated transmission development is causing an increase in visual impacts on both scenic and historic/cultural resources. This increase has highlighted the need for better integration of visual and historic/cultural resource assessment and management activities for land use planning purposes. The US Department of the Interior National Park Service (NPS), in response to concerns arising from potential scenic impacts from renewable energy, electric transmission, and other types of development on lands and waters near NPS units, has developed a VRI process for high-value views both within and outside NPS unit boundaries. The NPS VRI incorporates historic and cultural elements and values into the scenic resource inventory process and provides practical guidance and metrics for successfully integrating historic and cultural concerns into the NPS’s scenic resource conservation efforts. This article describes the NPS VRI process and compares it with the VRI processes of the US Department of the Interior Bureau of Land Management and the US Department of Agriculture Forest Service, with respect to the incorporation of historic and cultural values. The article discusses why a scenic inventory approach that more robustly integrates the historic and cultural values of the landscape is essential for NPS landscapes, and for fulfillment of NPS’s mission. Inventories are underway at many NPS units, and the results indicate that the VRI process can be used successfully to capture important historic and cultural resource information and incorporate that information into the assessment of the scenic values of views within and outside NPS units. Environmental Practice 18: 166–179 (2016)

cultural↗
DOE OSTI2025

Denoising Autoencoder for Reconstructing Sensor Observation Data and Predicting Evapotranspiration: Noisy and Missing Values Repair and Uncertainty Quantification

Abstract Machine learning (ML) methods applied in scientific research often deal with interrelated features in high‐dimensional data. Reducing data noise and redundancy is needed to increase prediction accuracy and efficiency especially when dealing with data from field sensors. We explored an unsupervised learning method, the denoising autoencoder (DAE), to extract the underlying data structure from noisy raw data in the context of predicting hydrologic quantities from multiple field sensors. These sensors have intrinsic instrumental noise and occasional malfunctions that cause missing values. Our DAE neural network reconstructed meteorological sensor data containing noise and missing values to predict evapotranspiration in a mountainous watershed. The DAE reconstructed the sensor variables with a mean coefficient of determination value of 0.77 across 15 dimensions representing individual sensors. It reduced variance and bias uncertainties compared to a classical autoencoder model. The reconstruction quality varied across dimensions depending on their cross‐correlation and alignment with the underlying data structure. Uncertainties arising from the model structure were overall higher than those resulting from data corruption. We attached the DAE structure to a downstream ET‐prediction neural network in three formats and achieved reasonably accurate ET predictions . The use of the DAE notably reduced variance uncertainty in ET prediction. However, excessive variance reduction may be accompanied by an increase in bias due to the intrinsic bias‐variance tradeoff. Our method of evaluating and reducing uncertainties in aggregated data from different sources can be used to improve predictive models, process understanding, and uncertainty quantification for better water resource management. Plain Language Summary We present a machine learning method, namely the denoising autoencoder, which reduces the effects of data noise and missing values typically present in scientific data sets collected through sensor measurements. This method selects the most relevant information from noisy raw data collected by the instruments and fills in missing values. To demonstrate the effectiveness of our method, we applied it to predict evapotranspiration, a hydrologic variable that represents the water moved from the land surface to the atmosphere through a combination of evaporation and plant water use (transpiration). We also used a random sampling technique (the Monte Carlo method) to compare the uncertainty in the predictions when using the raw and noisy data versus the reconstructed data. The denoising process produced more accurate predictions of evapotranspiration with less uncertainty. Improved predictions of evapotranspiration can lead to a better understanding and accounting of water budgets. This ML approach is broadly suitable for a wide variety of applications that involve noisy sensor data with missing values. Key Points We used a denoising autoencoder (DAE) neural network to reduce noise in meteorological and soil sensor observations by on average We used Monte Carlo sampling to estimate the bias and variance of all model outputs, including uncertainty sources from data and the model We attached the DAE component to a downstream neural network to predict ET with the variance reduced by , compared to that without the DAE

denoising autoencoder↗
DOE OSTI2025

Electric transmission value and its drivers in United States power markets

Electric transmission infrastructure plays a vital role during extreme weather and supply disruptions and can enable low-cost electricity systems. This paper contributes to a more complete understanding of the value and cost-effectiveness of transmission, as well as barriers to its development. By studying wholesale energy market prices in the United States between 2012 and 2022, we find that additional transfer capacity between regions would have been especially valuable, with a median value of $116 million per GW per year. This capacity would often have provided balanced benefits to each region. The market value of transmission was highly influenced by a small fraction of time: 5% of hours typically captured at least 45% of the total value. These peak periods were primarily driven by unforeseen changes in conditions within one day of operations. Annualized transmission infrastructure cost estimates were lower than the average market value for most locations, including all links crossing regional seams, where the value-to-cost ratio was often greater than 4. This suggests that there are barriers to developing valuable grid infrastructure. These results complement forward-looking modeling studies and support efforts to improve modeling practices.

Energy economics↗
DOE OSTI2024

Ultrafast Bragg coherent diffraction imaging of epitaxial thin films using deep complex-valued neural networks

Abstract Domain wall structures form spontaneously due to epitaxial misfit during thin film growth. Imaging the dynamics of domains and domain walls at ultrafast timescales can provide fundamental clues to features that impact electrical transport in electronic devices. Recently, deep learning based methods showed promising phase retrieval (PR) performance, allowing intensity-only measurements to be transformed into snapshot real space images. While the Fourier imaging model involves complex-valued quantities, most existing deep learning based methods solve the PR problem with real-valued based models, where the connection between amplitude and phase is ignored. To this end, we involve complex numbers operation in the neural network to preserve the amplitude and phase connection. Therefore, we employ the complex-valued neural network for solving the PR problem and evaluate it on Bragg coherent diffraction data streams collected from an epitaxial La 2-x Sr x CuO 4 (LSCO) thin film using an X-ray Free Electron Laser (XFEL). Our proposed complex-valued neural network based approach outperforms the traditional real-valued neural network methods in both supervised and unsupervised learning manner. Phase domains are also observed from the LSCO thin film at an ultrafast timescale using the complex-valued neural network.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2014

Definition of the metric on the space clos{sub ∅}(X) of closed subsets of a metric space X and properties of mappings with values in clos{sub ∅}(R{sup n})

The paper is concerned with the extension of tests for superpositional measurability, Filippov's implicit function lemma and the Scorza Dragoni property to set-valued (and, as a corollary, to single-valued) mappings that fail to satisfy the Carathéodory conditions (the upper Carathéodory conditions) and are not continuous (upper semicontinuous) in the phase variable. The corresponding results depend on the introduction of the space clos{sub ∅}(X) of all closed subsets (including the empty set) of an arbitrary metric space X; a metric on clos{sub ∅}(X) is proposed; the space clos{sub ∅}(X) is shown to be complete whenever the original space X is; a criterion for convergence of a sequence is put forward; mappings with values in clos{sub ∅}(X) are studied. Some results on set-valued mappings satisfying the Carathéodory conditions and having compact values in R{sup n} are shown to hold for mappings with values in clos{sub ∅}(R{sup n}), measurable in the first argument, and continuous in the proposed metric in the second argument. Bibliography: 22 titles.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2011

THE POSTERIOR DISTRIBUTION OF sin(i) VALUES FOR EXOPLANETS WITH M{sub T} sin(i) DETERMINED FROM RADIAL VELOCITY DATA

Radial velocity (RV) observations of an exoplanet system giving a value of M{sub T} sin(i) condition (i.e., give information about) not only the planet's true mass M{sub T} but also the value of sin(i) for that system (where i is the orbital inclination angle). Thus, the value of sin(i) for a system with any particular observed value of M{sub T} sin(i) cannot be assumed to be drawn randomly from a distribution corresponding to an isotropic i distribution, i.e., the presumptive prior distribution. Rather, the posterior distribution from which it is drawn depends on the intrinsic distribution of M{sub T} for the exoplanet population being studied. We give a simple Bayesian derivation of this relationship and apply it to several 'toy models' for the intrinsic distribution of M{sub T} , on which we have significant information from available RV data in some mass ranges but little or none in others. The results show that the effect can be an important one. For example, even for simple power-law distributions of M{sub T} , the median value of sin(i) in an observed RV sample can vary between 0.860 and 0.023 (as compared to the 0.866 value for an isotropic i distribution) for indices of the power law in the range between -2 and +1, respectively. Over the same range of indices, the 95% confidence interval on M{sub T} varies from 1.0001-2.405 ({alpha} = -2) to 1.13-94.34 ({alpha} = +2) times larger than M{sub T} sin(i) due to sin(i) uncertainty alone. More complex, but still simple and plausible, distributions of M{sub T} yield more complicated and somewhat unintuitive posterior sin(i) distributions. In particular, if the M{sub T} distribution contains any characteristic mass scale M{sub c} , the posterior sin(i) distribution will depend on the ratio of M{sub T} sin(i) to M{sub c} , often in a non-trivial way. Our qualitative conclusion is that RV studies of exoplanets, both individual objects and statistical samples, should regard the sin(i) factor as more than a 'numerical constant of order unity' with simple and well-understood statistical properties. We argue that reports of M{sub T} sin(i) determinations should be accompanied by a statement of the corresponding confidence bounds on M{sub T} at, say, the 95% level based on an explicitly stated assumed form of the true M{sub T} distribution in order to reflect more accurately the mass uncertainties associated with RV studies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

An Empirical Method for deriving RBE values associated with Electrons, Photons and Radionuclides

There is substantial evidence to justify using relative biological effectiveness (RBE) values greater than one for low-energy electrons and photons. But, in the field of radiation protection, radiation associated with low linear energy transfer (LET) has been assigned a radiation weighting factor w R of one. This value may be suitable for radiation protection but, for risk considerations, it is important to evaluate the potential elevated biological effectiveness of radiation to improve the quality of risk estimates. RBE values between 2 and 3 for tritium are implied by several experimental measurements. Additionally, elevated RBE values have been found for other similar low-energy radiation sources. In this work, RBE values are derived for electrons based upon the fractional deposition of absorbed dose of energies less than a few keV. Using this empirical method, RBE values were also derived for monoenergetic photons and 1070 radionuclides from ICRP Publication 107 for which photons and electrons are the primary emissions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2013

Stakeholder opinions on the use of the added value approach in siting radioactive waste management facilities

In some countries nuclear waste facility siting programs include social and economic benefits, compensation, local empowerment and motivation measures and other incentives for the potential host community. This can generally be referred to as an 'added value approach'. Demonstration of the safety of a repository is seen as a precondition of an added value approach. Recently much focus has been placed on studying and developing public participation approaches but less on the use of such incentive and community benefit packages, although they are becoming a more common element in many site selection strategies for nuclear waste management facilities. The primary objective of this paper is to report on an ongoing study of stakeholders' opinions of the use of an added value approach in siting a radioactive waste facility in the Czech Republic, Poland and Slovenia. The paper argues that an added value approach should adapt to the interests and needs of stakeholders during different stages of a siting process. The main question posed in the study is as follows: What are the measures which should be included in 'added value approach' according to the stakeholders? The research data consists of stakeholders' responses to a survey focusing on the use of added value (community benefits) and incentives in siting nuclear waste management facilities. The survey involved use of a questionnaire developed as part of the EU-funded IPPA* project in three countries: the Czech Republic, Poland and Slovenia. (* Implementing Public Participation Approaches in Radioactive Waste Disposal, FP7 Contract Number: 269849). The target audiences for the questionnaires were the stakeholders represented in the national stakeholder groups established to discuss site selection for a nuclear waste repository in their country. A total of 105 questionnaires were sent to the stakeholders between November 2011 and January 2012. 44 questionnaires were returned, resulting in a total response rate of 41% (10/29 in the Czech Republic, 11/14 in Poland and in 23/64 in Slovenia). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

SU-G-IeP2-12: The Effect of Iterative Reconstruction and CT Tube Voltage On Hounsfield Unit Values of Iodinated Contrast

Purpose: To investigate the effects of changing iterative reconstruction strength and tube voltage on Hounsfield Unit (HU) values of varying concentrations of Iodinated contrast medium in a phantom. Method: Iodinated contrast (Omnipaque 300, GE Healthcare, Princeton NJ) was diluted with distilled water to concentrations of 0.6, 0.9, 1.8, 3.6, 7.2, and 10.8 mg/mL of Iodine. The solutions were scanned in a patient equivalent water phantom on two MDCT scanners: VCT 64 slice (GE Medical Systems, Waukesha, WI) and an Aquilion One 320 slice scanner (Toshiba America Medical Systems, Tustin CA). The phantom was scanned at 80, 100, 120, 140 kV using 400, 255, 180, and 130 mAs, respectively, for the VCT scanner, and 80, 100, 120, and 135 kV using 400, 250, 200, and 150 mAs, respectively, on the Aquilion One. Images were reconstructed at 2.5 mm (VCT) and 0.5 mm (Aquilion One). The VCT images were reconstructed using Advanced Statistical Iterative Reconstruction (ASIR) at 6 different strengths: 0%, 20%, 40%, 60%, 80%, and 100%. Aquilion One images were reconstructed using Adaptive Iterative Dose Reduction (AIDR) at 4 strengths: no AIDR, Weak AIDR, Standard AIDR, and Strong AIDR. Regions of interest (ROIs) were drawn on the images to measure the HU values and standard deviations of the diluted contrast. Second order polynomials were used to fit the HU values as a function of Iodine concentration. Results: For both scanners, there was no significant effect of changing the iterative reconstruction strength. The polynomial fits yielded goodness-of-fit (R2) values averaging 0.997. Conclusion: Changing the strength of the iterative reconstruction has no significant effect on the HU values of Iodinated contrast in a tissue-equivalent phantom. Fit values of HU vs Iodine concentration are useful in quantitative imaging protocols such as the determination of cardiac output from time-density curves in the main pulmonary artery.

60 APPLIED LIFE SCIENCES↗