Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Reliability analysis”

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.

At least 1,117 records · Page 62
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Distinction of saffron cod ( Eleginus gracilis ) from several other gadid species by using microsatellite markers

Nine microsatellite loci isolated in saffron cod ( Eleginus gracilis ) have potential applications for population genetics. Polymerase chain reaction products of samples of E. gracilis from northwestern Alaska amplified reliably, produced only one or two microsatellite bands, and had no apparent homozygote excess. A collection of E. gracilis sampled in the Gulf of Alaska (GOA) near Kodiak Island did not amplify reliably at one locus, and allele frequency profiles clustered distinctly (with principal component analysis [PCA]) from the northwestern Alaska collection. Northwestern Alaska and GOA E. gracilis collections were genetically different (on the basis of a standardized genetic differentiation measure [ G ' ST ]=0.313, chord distance [ D chord ]=0.078, P<0.0001) and differed in expected aver-age heterozygosities at shared loci (0.859 and 0.689, respectively). We tested the microsatellite primers on other gadid species endemic to the northern Pacific Ocean, Bering Sea, and Arctic Ocean for cross-species amplification. Not all loci amplified reliably in navaga ( E. nawaga ), Pacific tomcod ( Microgadus proximus ), Arctic cod ( Boreogadus saida ), Pacific cod ( Gadus macrocephalus ), or walleye pollock ( G. chalcogrammus ). Reliable loci varied in microsatellite size profiles and produced distinct PCA clusters and accurate genotype assignments that allowed accurate species identification. Furthermore the identifications support previous morphological and genetically determined systematic classifications and distinguished the geographically separated collections of E. gracilis .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Hybrid HEFA-HDCJ Process for the Production of Jet Fuel Blendstocks

The hydrotreatment of bio-oil derived from the pyrolysis and biocrude from hydrothermal liquefaction of lignocellulosic materials to produce hydrocarbons faces significant technological challenges, mainly due to the high reactivity and poor thermal stability of bio-oil, resulting in the formation of large quantities of coke. This problem has been addressed by existing PNNL patents with a two-step hydrotreatment technology in which the bio-oil is first stabilized with a noble hydrogenation metal (often Pt or Ru). Then, in the second step, the bio-oil is deoxygenated with a Ni-Mo or Co-Mo sulfide catalyst. The main problem with this approach is that the Pt/Ru catalysts deactivate easily in the presence of S or other impurities, which are commonly present in pyrolysis oils. In this project, we explored technological solutions to mitigate coke formation, avoiding the use of Pt/Ru catalysts. Our strategy is based on three actions: (1) Bio-oil stabilization in the presence of alcohols. In this project, we studied the stabilization with butanol. (2) the use of a cosolvent to solubilize the bio-oil. Because coke formation reactions are second-order reactions a reduction in the concentration of reactive bio-oil molecules. In this case, we used yellow greases as a co-solvent. (3) Separation of bio-oil reactive fractions. In this project, we studied the removal of water-soluble fractions. Our batch co-hydrotreatment studies confirmed that the addition of butanol and methanol and the blend with lipids effectively contributed to mitigating coke formation (reducing coke yield to about 1 wt.% %). The removal of sugars did not have a noticeable effect on the overall coke yield, suggesting that coke precursors are present in all bio-oil fractions. Our analytical work suggests that they may be concentrated in the water-insoluble/CH 2 Cl 2 insoluble fractions of pyrolysis oils. Although the technological strategies tested resulted in significant coke reductions, the levels achieved were not sufficiently low to ensure a reliable operation in continuous, fixed-bed trickle-bed reactors. Long runs of more than 100 hours (maximum: 255 h) of co-processing time on stream were achieved in a continuous 40 mL reactor. When the same test was conducted in a larger 400 mL reactor, pressure drop increases associated with coke formation were observed. This increase in coke formation could be due to larger temperature gradients in the bed. Hydrodeoxygenation tests in moving bed reactors and using more active hydrogenation catalysts (for example Ni) could lead to more reliable operations. Unfortunately, our team did not have access to such experimental setups. The technoeconomic analysis suggests that although alcohol use is an effective means to reduce coke formation, the use of alcohol increases production cost. Thus, its use needs to be minimized. A delicate balance needs to be found between the use of technological solutions that allow the reliable operation of the system (stabilization with Ni catalysts, use of small quantities of solvents, processing in moving bed reactors) with a tolerable level of coke formation for the hydrodeoxygenation reactor used and that result in minimum production costs.

09 BIOMASS FUELS↗
DOE OSTI2020

Advances in soft X-ray RIXS for studying redox reaction states in batteries

Redox (reduction and oxidation) chemistry provides the fundamental basis for numerous energy-related electrochemical devices. Detecting the electrochemical redox chemistry is pivotal but challenging because it requires independent probes of the cationic and anionic redox states at different electrochemical states. Here, the synchrotron-based soft X-ray mapping of resonant inelastic X-ray scattering (mRIXS) has recently emerged as a powerful tool for exploring such states in electrochemical devices, especially batteries. High-efficiency mRIXS covers the energy range of the absorption edge with the extra dimension of information on the emitted photon energies. In this frontier article, we review recent representative demonstrations of utilizing soft X-ray mRIXS for detecting the novel chemical state during electrochemical operation and for quantifying the cationic redox reactions through inverse partial fluorescence yield analysis (mRIXS-iPFY). More importantly, the non-divalent states of oxygen in electrodes involving oxygen redox reactions could be reliably captured by mRIXS, with its reversibility quantified by the intensity variation of the characteristic mRIXS feature through a super-partial fluorescence yield analysis (mRIXS-sPFY). These recent demonstrations inspire future perspectives on using mRIXS for studying the complex phenomena in energy materials, with both technical and scientific challenges in RIXS theory, in situ/operando experiments, and spatially resolved RIXS imaging.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Dynamic Heat Flow and Current Distribution Analysis in the Bottom Anode of an Electric Arc Furnace Using Fiber-Optic Sensors

A reliable method for monitoring bottom anode wear during DC Electric Arc Furnace (DC-EAF) operation is of critical importance for safe and efficient steel production. Underestimation of bottom wear poses a serious safety risk that must be avoided, while overestimation of bottom wear also poses challenges, as premature anode replacement is expensive and affects EAF productivity. Previously, we demonstrated that fiber-optic sensors can be successfully deployed to create a spatially distributed temperature map to monitor the health of the anode. The present work explores the heat flow and current density distribution in bottom anode pins to predict bottom wear, steel penetration events, and monitor refractory erosion. Small dynamic variations in pin temperature induced by joule heating during arcing also provide a means to observe local current flows in each pin. When mapped, these measurements provide a real-time view of the non-uniform and dynamic current flow in the bottom anode during EAF operation that can affect bottom wear.

Bottom Anode↗
DOE OSTI2014

SU-C-9A-02: Structured Noise Index as An Automated Quality Control for Nuclear Medicine: A Two Year Experience

Purpose: Flood-field uniformity evaluation is an essential element in the assessment of nuclear medicine (NM) gamma cameras. It serves as the central element of the quality control (QC) program, acquired and analyzed on a daily basis prior to clinical imaging. Uniformity images are traditionally analyzed using pixel value-based metrics which often fail to capture subtle structure and patterns caused by changes in gamma camera performance requiring additional visual inspection which is subjective and time demanding. The goal of this project was to develop and implement a robust QC metrology for NM that is effective in identifying non-uniformity issues, reporting issues in a timely manner for efficient correction prior to clinical involvement, all incorporated into an automated effortless workflow, and to characterize the program over a two year period. Methods: A new quantitative uniformity analysis metric was developed based on 2D noise power spectrum metrology and confirmed based on expert observer visual analysis. The metric, termed Structured Noise Index (SNI) was then integrated into an automated program to analyze, archive, and report on daily NM QC uniformity images. The effectiveness of the program was evaluated over a period of 2 years. Results: The SNI metric successfully identified visually apparent non-uniformities overlooked by the pixel valuebased analysis methods. Implementation of the program has resulted in nonuniformity identification in about 12% of daily flood images. In addition, due to the vigilance of staff response, the percentage of days exceeding trigger value shows a decline over time. Conclusion: The SNI provides a robust quantification of the NM performance of gamma camera uniformity. It operates seamlessly across a fleet of multiple camera models. The automated process provides effective workflow within the NM spectra between physicist, technologist, and clinical engineer. The reliability of this process has made it the preferred platform for NM uniformity analysis.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2016

Residential Cold Climate Heat Pump (CCHP) w/Variable Speed Technology

This report summarizes the results of a three year program awarded to Unico, Inc. to commercialize a residential cold climate heat pump. Several designs were investigated. Compressors were selected using analysis from Oakridge National Laboratories followed by prototype construction and lab testing in a specially built environmental chamber capable of reaching -30°F. The initial design utilized two variable speed compressors in series with very good capacity results and acceptable efficiency at very cold temperatures. The design was then modified to reduce cost and complexity by redesigning the system using three dual-stage compressors: two in parallel followed by one in series. Extensive testing found significant challenge with oil management, reliability, weight and cost which prevented the system from being fully commercialized. Further analysis of other conceptual designs indicated that these challenges could be overcome in the future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

Evaluation of MRI and cannabinoid type 1 receptor PET templates constructed using DARTEL for spatial normalization of rat brains

Purpose: Image registration is one prerequisite for the analysis of brain regions in magnetic-resonance-imaging (MRI) or positron-emission-tomography (PET) studies. Diffeomorphic anatomical registration through exponentiated Lie algebra (DARTEL) is a nonlinear, diffeomorphic algorithm for image registration and construction of image templates. The goal of this small animal study was (1) the evaluation of a MRI and calculation of several cannabinoid type 1 (CB1) receptor PET templates constructed using DARTEL and (2) the analysis of the image registration accuracy of MR and PET images to their DARTEL templates with reference to analytical and iterative PET reconstruction algorithms. Methods: Five male Sprague Dawley rats were investigated for template construction using MRI and [{sup 18}F]MK-9470 PET for CB1 receptor representation. PET images were reconstructed using the algorithms filtered back-projection, ordered subset expectation maximization in 2D, and maximum a posteriori in 3D. Landmarks were defined on each MR image, and templates were constructed under different settings, i.e., based on different tissue class images [gray matter (GM), white matter (WM), and GM + WM] and regularization forms (“linear elastic energy,” “membrane energy,” and “bending energy”). Registration accuracy for MRI and PET templates was evaluated by means of the distance between landmark coordinates. Results: The best MRI template was constructed based on gray and white matter images and the regularization form linear elastic energy. In this case, most distances between landmark coordinates were <1 mm. Accordingly, MRI-based spatial normalization was most accurate, but results of the PET-based spatial normalization were quite comparable. Conclusions: Image registration using DARTEL provides a standardized and automatic framework for small animal brain data analysis. The authors were able to show that this method works with high reliability and validity. Using DARTEL templates together with nonlinear registration algorithms allows for accurate spatial normalization of combined MRI/PET or PET-only studies.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

TU-FG-201-01: 18-Month Clinical Experience of a Linac Daily Quality Assurance (QA) Solution Using Only EPID and OBI

Purpose: To describe the clinical use of a Linear Accelerator (Linac) DailyQA system with only EPID and OBI. To assess the reliability over an 18-month period and improve the robustness of this system based on QA failure analysis. Methods: A DailyQA solution utilizing an in-house designed phantom, combined EPID and OBI image acquisitions, and a web-based data analysis and reporting system was commissioned and used in our clinic to measure geometric, dosimetry and imaging components of a Varian Truebeam Linac. During an 18-month period (335 working days), the Daily QA results, including the output constancy, beam flatness and symmetry, uniformity, TPR20/10, MV and KV imaging quality, were collected and analyzed. For output constancy measurement, an independent monthly QA system with an ionization chamber (IC) and annual/incidental TG51 measurements with ADCL IC were performed and cross-compared to Daily QA system. Thorough analyses were performed on the recorded QA failures to evaluate the machine performance, optimize the data analysis algorithm, adjust the tolerance setting and improve the training procedure to prevent future failures. Results: A clinical workflow including beam delivery, data analysis, QA report generation and physics approval was established and optimized to suit daily clinical operation. The output tests over the 335 working day period cross-correlated with the monthly QA system within 1.3% and TG51 results within 1%. QA passed with one attempt on 236 days out of 335 days. Based on the QA failures analysis, the Gamma criteria is revised from (1%, 1mm) to (2%, 1mm) considering both QA accuracy and efficiency. Data analysis algorithm is improved to handle multiple entries for a repeating test. Conclusion: We described our 18-month clinical experience on a novel DailyQA system using only EPID and OBI. The long term data presented demonstrated the system is suitable and reliable for Linac daily QA.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

On the accretion rates and radiative efficiencies of the highest-redshift quasars

We estimate the accretion rates onto the supermassive black holes that power 20 of the highest-redshift quasars, at z≳5.8, including the quasar with the highest redshift known to date—ULAS J1120 at z = 7.09. The analysis is based on the observed (rest-frame) optical luminosities and reliable “virial” estimates of the BH masses of the quasars, and utilizes scaling relations derived from thin accretion disk theory. The mass accretion rates through the postulated disks cover a wide range, M-dot {sub disk}≃4--190 M{sub ⊙} yr{sup −1}, with most of the objects (80%) having M-dot {sub disk}≃10--65 M{sub ⊙} yr{sup −1}, confirming the Eddington-limited nature of the accretion flows. By combining our estimates of M-dot {sub disk} with conservative, lower limits on the bolometric luminosities of the quasars, we investigate which alternative values of η best account for all the available data. We find that the vast majority of quasars (∼85%) can be explained with radiative efficiencies in the range η≃0.03--0.3, with a median value close to the commonly assumed η = 0.1. Within this range, we obtain conservative estimates of η≳0.14 for ULAS J1120 and SDSS J0100 (at z = 6.3), and of ≳0.19 for SDSS J1148 (at z=6.41; assuming their BH masses are accurate). The implied accretion timescales are generally in the range t{sub acc}≡M{sub BH}/ M-dot {sub BH}≃0.1--1 Gyr, suggesting that most quasars could have had ∼1--10 mass e-foldings since BH seed formation. Our analysis therefore demonstrates that the available luminosities and masses for the highest-redshift quasars can be explained self-consistently within the thin, radiatively efficient accretion disk paradigm. Episodes of radiatively inefficient, “super-critical” accretion may have occurred at significantly earlier epochs (i.e., z≳10).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2015

Model-Based Integrated High Penetration Renewables Planning and Control Analysis

Increasing adoption of Solar Photovoltaic (PV) generation at the distribution level poses several changes for the reliable operation of electrical power distribution systems. The addition of a significant amount of PV to a distribution network can introduce a variety of operational problems, including steady-state overvoltages, reverse flows, voltage flicker and excessive controller movement among others. These adverse impacts can be mitigated through a variety of equipment upgrades which represent a cost to either the electric utility or the owner of the PV site. The study performed here aims to quantify the levels of PV generation which present operational problems on a distribution circuit and how those problems might be alleviated. The study performed here included 20 distribution feeders selected from Pepco Holdings, Inc. (PHI) service territory. These feeders are located in the states of Delaware, Maryland and New Jersey. A hosting capacity study was performed on each feeder to determine how much additional PV it could support in its current configuration. Several improvements were then performed on these circuits including phase balancing, capacitor redesign, reducing the voltage regulator set points, fixed power factor operation on the PV inverters and the installation of battery storage. After each of these improvements the hosting capacity of the circuit was reevaluated in order to determine how that particular improvement impacted the amount of PV that could be hosted by the circuit. Each of these improvements represents a real cost in terms of labor and equipment in order to be implemented. They are expected to provide a benefit in terms of the amount of additional PV generation which can be safely interconnected to the distribution feeder. A cost benefit analysis was performed in order to evaluate the expected costs of each feeder improvement and how each one was able to increase the PV hosting capacity of each feeder. It is hoped that these results can be utilized by other distribution utilities in order to understand how they can improve the hosting capacity of their feeders and facilitate the deployment of more PV generation at the distribution level. Admittedly other utility companies will most likely have different feeder architectures and differing labor and equipment costs so the realized cost benefit numbers may be significantly different.

14 SOLAR ENERGY↗
DOE OSTI2012

Prognostic Health Monitoring System: Component Selection Based on Risk Criteria and Economic Benefit Assessment

Prognostic health monitoring (PHM) is a proactive approach to monitor the ability of structures, systems, and components (SSCs) to withstand structural, thermal, and chemical loadings over the SSCs planned service lifespans. The current efforts to extend the operational license lifetime of the aging fleet of U.S. nuclear power plants from 40 to 60 years and beyond can benefit from a systematic application of PHM technology. Implementing a PHM system would strengthen the safety of nuclear power plants, reduce plant outage time, and reduce operation and maintenance costs. However, a nuclear power plant has thousands of SSCs, so implementing a PHM system that covers all SSCs requires careful planning and prioritization. This paper therefore focuses on a component selection that is based on the analysis of a component's failure probability, risk, and cost. Ultimately, the decision on component selection depend on the overall economical benefits arising from safety and operational considerations associated with implementing the PHM system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Extending the predictive power of perturbative QCD using the principle of maximum conformality and the Bayesian analysis

In addition to the evaluation of high-order loop contributions, the precision and predictive power of perturbative QCD (pQCD) predictions depends on two important issues: (1) how to achieve a reliable, convergent fixed-order series, and (2) how to reliably estimate the contributions of unknown higher-order terms. The recursive use of renormalization group equation, together with the Principle of Maximum Conformality (PMC), eliminates the renormalization scheme-and-scale ambiguities of the conventional pQCD series. The result is a conformal, scale-invariant series of finite order which also satisfies all of the principles of the renormalization group. In this paper we propose a novel Bayesian-based approach to estimate the size of the unknown higher order contributions based on an optimized analysis of probability distributions. We show that by using the PMC conformal series, in combination with the Bayesian analysis, one can consistently achieve high degree of reliability estimates for the unknown high order terms. Thus the predictive power of pQCD can be greatly improved. We illustrate this procedure for two pQCD observables: R e+e– and R τ , which are each known up to four loops in pQCD. Numerical analyses confirm that by using the scale-independent and more convergent PMC conformal series, one can achieve reliable Bayesian probability estimates for the unknown higher-order contributions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

The IEC 61850 Sampled Measured Values Protocol: Analysis, Threat Identification, and Feasibility of Using NN Forecasters to Detect Spoofed Packets

The operation of the smart grid is anticipated to rely profoundly on distributed microprocessor-based control. Therefore, interoperability standards are needed to address the heterogeneous nature of the smart grid data. Since the IEC 61850 emerged as a wide-spread interoperability standard widely accepted by the industry, the Sampled Measured Values method has been used to communicate digitized voltage and current measurements. Realizing that current and voltage measurements (i.e., feedback measurements) are necessary for reliable and secure noperation of the power grid, firstly, this manuscript provides a detailed analysis of the Sampled Measured Values protocol emphasizing its advantages, then, it identifies vulnerabilities in this protocol and explains the cyber threats associated to these vulnerabilities. Secondly, current efforts to mitigate these vulnerabilities are outlined and the feasibility of using neural network forecasters to detect spoofed sampled values is investigated. It was shown that although such forecasters have high spoofed data detection accuracy, they are prone to the accumulation of forecasting error. Accordingly, this paper also proposes an algorithm to detect the accumulation of the forecasting error based on lightweight statistical indicators. The effectiveness of the proposed methods is experimentally verified in a laboratory-scale smart grid testbed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

High-Performance Computing for Real-Time Grid Analysis and Operation

Power grids worldwide are undergoing an unprecedented transition as a result of grid evolution meeting information revolution. The grid evolution is largely driven by the desire for green energy. Emerging grid technologies such as renewable generation, smart loads, plug-in hybrid vehicles, and distributed generation provide opportunities to generate energy from green sources and to manage energy use for better system efficiency. With utility companies actively deploying these technologies, a high level of penetration of these new technologies is expected in the next 5-10 years, bringing in a level of intermittency, uncertainties, and complexity that the grid did not see nor design for. On the other hand, the information infrastructure in the power grid is being revolutionized with large-scale deployment of sensors and meters in both the transmission and distribution networks. The future grid will have two-way flows of both electrons and information. The challenge is how to take advantage of the information revolution: pull the large amount of data in, process it in real time, and put information out to manage grid evolution. Without addressing this challenge, the opportunities in grid evolution will remain unfulfilled. This transition poses grand challenges in grid modeling, simulation, and information presentation. The computational complexity of underlying power grid modeling and simulation will significantly increase in the next decade due to an increased model size and a decreased time window allowed to compute model solutions. High-performance computing is essential to enable this transition. The essential technical barrier is to vastly increase the computational speed so operation response time can be reduced from minutes to seconds and sub-seconds. The speed at which key functions such as state estimation and contingency analysis are conducted (typically every 3-5 minutes) needs to be dramatically increased so that the analysis of contingencies is both comprehensive and real time. An even bigger challenge is how to incorporate dynamic information into real-time grid operation. Today’s online grid operation is based on a static grid model and can only provide a static snapshot of current system operation status, while dynamic analysis is conducted offline because of low computational efficiency. The offline analysis uses a worst-case scenario to determine transmission limits, resulting in under-utilization of grid assets. This conservative approach does not necessarily lead to reliability. Many times, actual power grid scenarios are not studied, and they will push the grid over the edge and resulting in outages and blackouts. This chapter addresses the HPC needs in power grid analysis and operations. Example applications such as state estimation and contingency analysis are given to demonstrate the value of HPC in power grid applications. Future research directions are suggested for high performance computing applications in power grids to improve the transparency, efficiency, and reliability of power grids.

Contingency Analysis↗
DOE OSTI2022

Machine learning for ultrasonic nondestructive examination of welding defects: A systematic review

Recent years have seen a substantial increase in the application of machine learning (ML) for automated analysis of nondestructive examination (NDE) data. One of the applications of interest is the use of ML for the analysis of data from in-service inspection of welds in nuclear power and other industries. These types of inspections are performed in accordance with criteria described in the ASME Boiler and Pressure Vessel Code and require the use of reliable NDE techniques. The rapid growth in ML methods and the diversity of possible approaches indicate a need to assess the current capabilities of ML and automated data analysis for NDE and identify any gaps or shortcomings in current ML technologies as applied to the automated analysis of NDE data. In particular, there is a need to determine the impact of ML on the NDE reliability. This paper discusses the findings from a literature survey on the current state of ML for the automated analysis of data from ultrasonic NDE of weld flaws. It discusses an overview of ultrasonic NDE as used for weld inspections in nuclear power and other industries. Herein, data sets and ML models used in the literature are summarized, along with a generally applicable workflow for ML. Findings on the capabilities, limitations and potential gaps in feature selection, data selection, and ML model optimization are discussed. The paper identified several needs for quantifying and validating the performance of ML methods for ultrasonic NDE, including the need for common data sets.

36 MATERIALS SCIENCE↗
DOE OSTI2016

SU-F-R-40: Robustness Test of Computed Tomography Textures of Lung Tissues to Varying Scanning Protocols Using a Realistic Phantom Environment

Purpose: The reliability of computed tomography (CT) textures is an important element of radiomics analysis. This study investigates the dependency of lung CT textures on different breathing phases and changes in CT image acquisition protocols in a realistic phantom setting. Methods: We investigated 11 CT texture features for radiation-induced lung disease from 3 categories (first-order, grey level co-ocurrence matrix (GLCM), and Law’s filter). A biomechanical swine lung phantom was scanned at two breathing phases (inhale/exhale) and two scanning protocols set for PET/CT and diagnostic CT scanning. Lung volumes acquired from the CT images were divided into 2-dimensional sub-regions with a grid spacing of 31 mm. The distribution of the evaluated texture features from these sub-regions were compared between the two scanning protocols and two breathing phases. The significance of each factor on feature values were tested at 95% significance level using analysis of covariance (ANCOVA) model with interaction terms included. Robustness of a feature to a scanning factor was defined as non-significant dependence on the factor. Results: Three GLCM textures (variance, sum entropy, difference entropy) were robust to breathing changes. Two GLCM (variance, sum entropy) and 3 Law’s filter textures (S5L5, E5L5, W5L5) were robust to scanner changes. Moreover, the two GLCM textures (variance, sum entropy) were consistent across all 4 scanning conditions. First-order features, especially Hounsfield unit intensity features, presented the most drastic variation up to 39%. Conclusion: Amongst the studied features, GLCM and Law’s filter texture features were more robust than first-order features. However, the majority of the features were modified by either breathing phase or scanner changes, suggesting a need for calibration when retrospectively comparing scans obtained at different conditions. Further investigation is necessary to identify the sensitivity of individual image acquisition parameters.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Chisel: reliability- and accuracy-aware optimization of approximate computational kernels

The accuracy of an approximate computation is the distance between the result that the computation produces and the corresponding fully accurate result. The reliability of the computation is the probability that it will produce an acceptably accurate result. Emerging approximate hardware platforms provide approximate operations that, in return for reduced energy consumption and/or increased performance, exhibit reduced reliability and/or accuracy. We present Chisel, a system for reliability- and accuracy-aware optimization of approximate computational kernels that run on approximate hardware platforms. Given a combined reliability and/or accuracy specification, Chisel automatically selects approximate kernel operations to synthesize an approximate computation that minimizes energy consumption while satisfying its reliability and accuracy specification. We evaluate Chisel on five applications from the image processing, scientific computing, and financial analysis domains. The experimental results show that our implemented optimization algorithm enables Chisel to optimize our set of benchmark kernels to obtain energy savings from 8.7% to 19.8% compared to the fully reliable kernel implementations while preserving important reliability guarantees.

97 MATHEMATICS AND COMPUTING↗