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Randolph, VT, United States

Ebelhar R.J.,Terracon Consultants Inc. | Du J.D.,Terracon Consultants Inc. | Beckett D.P.,Kentucky Transportation Cabinet | Dimaggio J.A.,Applied Research Assoc
Geotechnical Special Publication | Year: 2015

A design-phase pile load test program has been performed to study the constructability and design parameters for large-diameter steel pipe piles for the proposed Kentucky Lake Bridge as part of the US68/KY 80 Bridge over Kentucky Lake project in Marshall and Trigg Counties, Kentucky. The pile load test program included a 26.7-MN (6000-kip) static axial pile load test, 26.7- and 37.8-MN (6000- and 8500-kip) axial pseudo-static pile load tests, a 1.87 MN (420-kip) lateral pseudo-static pile load test and dynamic pile testing on six large-diameter pipe piles in difficult soil conditions. The pile load test program confirmed that the proposed 1.22- and 1.83-meter-diameter (48- and 72-inch-diameter) steel pipe piles with wall thicknesses ranging from 25 to 51 mm (1 to 2 in.) could be installed to the anticipated target nominal resistances and respective elevations at the site using a Menck MHU800S hydraulic hammer. The pile load test program indicated that the proposed steel constrictor plates should be installed within the pipe piles to increase bearing resistance, and helped the design team to gather information regarding viable design of the constrictor plates, how to locate the constrictor plates relative to the pile tip location, and in what soil strata the constrictor plates should bear within to mobilize additional bearing resistance in the pile design. Axial static and pseudo-static pile load testing indicated that the skin resistance values used in the pile design phase were valid and likely somewhat conservative and indicated that the 1.22-meter-diameter (48-inch-diameter) piles were more likely to achieve a plugged condition. © ASCE 2015. Source


Sugarman S.L.,Oak Ridge Assoc Universities | Livingston G.K.,Oak Ridge Assoc Universities | Stricklin D.L.,Applied Research Assoc | Abbott M.G.,Oak Ridge Assoc Universities | And 12 more authors.
Health Physics | Year: 2014

Response to a large-scale radiological incident could require timely medical interventions to minimize radiation casualties. Proper medical care requires knowing the victim's radiation dose. When physical dosimetry is absent, radiation-specific chromosome aberration analysis can serve to estimate the absorbed dose in order to assist physicians in the medical management of radiation injuries. A mock exercise scenario was presented to six participating biodosimetry laboratories as one individual acutely exposed to Co under conditions suggesting whole-body exposure. The individual was not wearing a dosimeter and within 2-3 h of the incident began vomiting. The individual also had other medical symptoms indicating likelihood of a significant dose. Physicians managing the patient requested a dose estimate in order to develop a treatment plan. Participating laboratories in North and South America, Europe, and Asia were asked to evaluate more than 800 electronic images of metaphase cells from the patient to determine the dicentric yield and calculate a dose estimate with 95% confidence limits. All participants were blind to the physical dose until after submitting their estimates based on the dicentric chromosome assay (DCA). The exercise was successful since the mean biological dose estimate was 1.89 Gy whereas the actual physical dose was 2 Gy. This is well within the requirements for guidance of medical management. The exercise demonstrated that the most labor-intensive step in the entire process (visual evaluation of images) can be accelerated by taking advantage of world-wide expertise available on the Internet. © 2014 Health Physics Society. Source


Grady D.E.,Applied Research Assoc
Journal of Applied Physics | Year: 2015

A fourth-power law underlying the steady shock-wave structure and solid viscosity of condensed material has been observed for a wide range of metals and non-metals. The fourth-power law relates the steady-wave Hugoniot pressure to the fourth power of the strain rate during passage of the material through the structured shock wave. Preceding the fourth-power law was the observation in a shock transition that the product of the shock dissipation energy and the shock transition time is a constant independent of the shock pressure amplitude. Invariance of this energy-time product implies the fourth-power law. This property of the shock transition in solids was initially identified as a shock invariant. More recently, it has been referred to as the dissipative action, although no relationship to the accepted definitions of action in mechanics has been demonstrated. This same invariant property has application to a wider range of transient failure phenomena in solids. Invariance of this dissipation action has application to spall fracture, failure through adiabatic shear, shock compaction of granular media, and perhaps others. Through models of the failure processes, a clearer picture of the physics underlying the observed invariance is emerging. These insights in turn are leading to a better understanding of the shock deformation processes underlying the fourth-power law. Experimental result and material models encompassing the dynamic failure of solids are explored for the purpose of demonstrating commonalities leading to invariance of the dissipation action. Calculations are extended to aluminum and uranium metals with the intent of predicting micro-scale dynamics and spatial structure in the steady shock wave. © 2015 AIP Publishing LLC. Source


Grant
Agency: National Aeronautics and Space Administration | Branch: | Program: SBIR | Phase: Phase I | Award Amount: 49.79K | Year: 1992

N/A


Besaw L.E.,Applied Research Assoc | Stimac P.J.,Applied Research Assoc
Proceedings of SPIE - The International Society for Optical Engineering | Year: 2014

Buried explosive hazards (BEHs) have been, and continue to be, one of the most deadly threats in modern conflicts. Current handheld sensors rely on a highly trained operator for them to be effective in detecting BEHs. New algorithms are needed to reduce the burden on the operator and improve the performance of handheld BEH detectors. Traditional anomaly detection and discrimination algorithms use a feature extraction techniques to characterize and classify threats. In this work we use a Deep Belief Network (DBN) to transcend the traditional approaches of BEH detection (e.g., principal component analysis and real-time novelty detection techniques). DBNs are pretrained using an unsupervised learning algorithm to generate compressed representations of unlabeled input data and form feature detectors. They are then fine-tuned using a supervised learning algorithm to form a predictive model. Using ground penetrating radar (GPR) data collected by a robotic cart swinging a handheld detector, our research demonstrates that relatively small DBNs can learn to model GPR background signals and detect BEHs with an acceptable false alarm rate (FAR). In this work, our DBNs achieved 91% probability of detection (P d) with 1.4 false alarms per square meter when evaluated on anti-tank and anti-personnel targets at temperate and arid test sites. This research demonstrates that DBNs are a viable approach to detect and classify BEHs. © 2014 SPIE. Source

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