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Evaluation of Accuracy and Performance of a Bilinear Interpolator with Dense EOS Tables in xRage
This study investigates the performance and accuracy of simulations using air and deuterium equation-of-state (EOS) tables that have been densified coupled with linear interpolation, as opposed to the default rational interpolation used in EOSPAC. EOS tables that are densified by adding in more temperature and density points that have been calculated by the rational function interpolator are able to improve the accuracy of the linear interpolator by over 50%. There was no change in runtime performance for a simulation using a dense EOS table with linear interpolation. In a memory limited case, dense EOS tables had no apparent effect on the simulation runtime or memory usage.
Single event effects induced by heavy ions in SONOS charge trapping memory arrays.
Abstract not provided.
Machine parts recognition using a trinary associative memory
The convergence mechanism of vectors in Hopfield's neural network in relation to recognition of partially known patterns is studied in terms of both inner products and Hamming distance. It has been shown that Hamming distance should not always be used in determining the convergence of vectors. Instead, inner product weighting coefficients play a more dominant role in certain data representations for determining the convergence mechanism. A trinary neuron representation for associative memory is found to be more effective for associative recall. Applications of the trinary associative memory to reconstruct machine part images that are partially missing are demonstrated by means of computer simulation as examples of the usefulness of this approach.
Observation of the Kaiser Effect Using Noble Gas Release Signals
The Kaiser effect was defined in the early 1950s (Kaiser 1953) and was extensively reviewed and evaluated by Lavrov (2002) with a view toward understanding stress estimations. The Kaiser effect is a stress memory phenomenon which has most often been demonstrated in rock using acoustic emissions. During cyclic loading–unloading–reloading, the acoustic emissions are near zero until the load exceeds the level of the previous load cycle. Here, we sought to explore the Kaiser effect in rock using real-time noble gas release. Laboratory studies using real-time mass spectrometry measurements during deformation have quantified, to a degree, the types of gases released (Bauer et al. 2016a, b), their release rates and amounts during deformation, estimates of permeability created from pore structure modifications during deformation (Gardner et al. 2017) and the impact of mineral plasticity upon gas release. We found that noble gases contained in brittle crystalline rock are readily released during deformation.
Martensitic transformation and phase stability of In-doped Ni-Mn-Sn shape memory alloys from first-principles calculations
The effect of the alloying element Indium (In) on the martensitic transition, magnetic properties, and phase stabilities of Ni{sub 8}Mn{sub 6}Sn{sub 2−x}In{sub x} shape memory alloys has been investigated using the first-principles pseudopotential plane-wave method based on density functional theory. The energy difference between the austenitic and martensitic phases was found to increase with increasing In content, which implies an enhancement of the martensitic phase transition temperature (T{sub M}). Moreover, the formation energy results indicate that In-doping increases the relative stability of Ni{sub 8}Mn{sub 6}Sn{sub 2−x}In{sub x} both in austenite and martensite. This results from a reduction in density of states near the Fermi level regions caused by Ni-3d–In-5p hybridization when Sn is replaced by In. The equilibrium equation of state results show that the alloys Ni{sub 8}Mn{sub 6}Sn{sub 2−x}In{sub x} exhibit an energetically degenerated effect for an In content of x = ∼1.5. This implies the coexistence of antiparallel and parallel configurations in the austenite.
Shape memory behavior and recovery force of 4D printed textile functional composites
Four-dimensional (4D) printing of multi-directionally reinforced preforms has tremendous potential for the development of next generation functional composites by using the capabilities of 3D printing technology, 3D textile preform design, and polymer shape memory behavior. This paper demonstrates the shape memory behavior and recovery force of 4D printed circular braided tube preforms and their silicone elastomer matrix composites. The preforms were printed by fused deposition modeling using the shape memory polymer (SMP), polylactic acid (PLA). The effects of braiding angle, tube wall thickness, and shape recovery temperature on the shape memory behavior of 4D printed tube preforms and their silicone elastomer matrix composites have been characterized. Measurements of shape recovery forces of the preform and composite were conducted using dynamic mechanical analysis (DMA). The braided microstructural parameters and shape recovery temperature have a significant effect on the preform shape memory behavior. The introduction of the silicone elastomer matrix greatly enhances the shape recovery force, shape recovery ratio, as well as radial compressive failure load of the 4D printed preform/silicone elastomer matrix composite. Finally, building on these results, a potential application for 4D printed textile functional composites is presented.
Effect of laser welding parameters on the austenite and martensite phase fractions of NiTi
Although laser welding is probably the most used joining technique for NiTi shape memory alloys there is still a lack of understanding about the effects of laser welding parameters on the microstructural induced changes: in both the heat affected and fusion zones martensite may be present, while the base material is fully austenitic. Synchrotron X-ray diffraction was used for fine probing laser welded NiTi joints. Through Rietveld refinement the martensite and austenite phase fractions were determined and it was observed that the martensite content increases towards the weld centreline. This is related to a change of the local transformation temperatures on these regions, which occurs due to compositional variation in those regions. The martensite phase fraction in the thermally affected regions may have significant implications on functional properties on these joints. - Highlights: •Synchrotron X-ray diffraction was used for fine probing of the microstructure in laser welded NiTi joints. •Rietveld refinement allowed to determine the content of martensite along the heat affected and fusion zones. •The martensite content increases from the base material towards the weld centreline.
Effects of the interplay between atomic and magnetic order on the properties of metamagnetic Ni-Co-Mn-Ga shape memory alloys
Ni-Co-Mn-Ga ferromagnetic shape memory alloys show metamagnetic behavior for a range of Co contents. The temperatures of the structural and magnetic transitions depend strongly on composition and atomic order degree, in such a way that combined composition and thermal treatment allows obtaining martensitic transformation between any magnetic state of austenite and martensite. This work presents a detailed analysis of the effect of atomic order on Ni-Co-Mn-Ga alloys through the evolution of structural and magnetic transitions after quench from high temperatures and during post-quest ageing. It is found that the way in which the atomic order affects the martensitic transformation temperatures and entropy depends on the magnetic order of austenite and martensite. The results can be explained assuming that improvement of atomic order decreases the free energy of the structural phases according to their magnetic order. However, it is assumed in this work that changes in the slope—that is, the entropy—of the Gibbs free energy curves are also decisive to the stability of the two-phase system. The experimental transformation entropy values have been compared with a phenomenological model, based on a Bragg–Williams approximation, accounting for the magnetic contribution. The excellent agreement obtained corroborates the magnetic origin of changes in transformation entropy brought about by atomic ordering.
Transcranial stimulation over the left inferior frontal gyrus increases false alarms in an associative memory task in older adults
Here, transcranial direct current stimulation (tDCS) is a potent ial tool for alleviating various forms of cognitive decline, including memory loss, in older adults. However, past effects of tDCS on cognitive ability have been mixed. One important potential moderator of tDCS effects is the baseline level of cognitive performance. We tested the effects of tDCS on face-name associative memory in older adults, who suffer from performance deficits in this task relative to younger adults. Stimulation was applied to the left inferior prefrontal cortex during encoding of face-name pairs, and memory was assessed with both a recognition and recall task. As a result, face–name memory performance was decreased with the use of tDCS. This result was driven by increased false alarms when recognizing rearranged face–name pairs.
A brief review of spin glass magnetometry techniques
Spin glasses are inherently dynamical. Taken properly, measurements of these materials can capture their dynamics and provide a wealth of insight into the physics of the spin glass state. In this methods review, two magnetometry methods are directly compared–ac and dc. Because these measurements are taken differently, the resulting data of each method will contain different information about spin glass behavior. This review will specifically focus on how the out-of-equilibrium effects of aging, rejuvenation, and memory manifest in each of these techniques, and how to construct protocols to measure these effects. We then describe the physical significance of each type of measurement and how to interpret their results. Finally, we explicitly detail which applications are most appropriate for which method. This will help the reader select the most helpful technique to carry out their own future experiments.
Parallel k-means Clustering of Geospatial Data Sets Using Manycore CPU Architectures
The increasing availability of high-resolution geospatiotemporal data sets from sources such as observatory networks, remote sensing platforms, and computational Earth system models has opened new possibilities for knowledge discovery and mining of weather, climate, ecological, and other geoscientific data sets fused from disparate sources. Many of the standard tools used on individual workstations are impractical for the analysis and synthesis of data sets of this size; however, new algorithmic approaches that can effectively utilize the complex memory hierarchies and the extremely high levels of parallelism available in state-of-the-art high-performance computing platforms can enable such analysis. Here, we describe pKluster, an open-source tool we have developed for accelerated k-means clustering of geospatial and geospatiotemporal data, and discuss algorithmic modifications and code optimizations we have made to enable it to effectively use parallel machines based on novel CPU architectures—such as the Intel “Knights Landing” Xeon Phi and Skylake Xeon processors—with many cores and hardware threads, and employing significant single instruction, multiple data (SIMD) parallelism. We outline some applications of the code in ecology and climate science contexts and present a detailed discussion of the performance of the code for one such application, LiDAR-derived vertical vegetation structure classification.
Effects of Heat Input on Weld-Bead Geometry, Surface Chemical Composition, Corrosion Behavior and Thermal Properties of Fiber Laser-Welded Nitinol Shape Memory Alloy
Bead-on-plate laser welding was carried out on 1-mm-thick Nitinol sheets at different heat input values. The variations in weld-bead geometry and variations in microstructures across the bead were studied. The effects of heat input on surface layer composition of the welded samples, corrosion properties and phase transformation temperature were examined. From x-ray photoelectron spectroscopy (XPS), it was clear that relative intensity of elemental Ni peak was higher in parent material and the oxidation state of Ti was Ti{sup 4+}. It was further observed from Auger electron spectroscopy (AES) that the Ti to Ni ratio on the top surface of the welded samples was more than 1, and as a result of this the stability of TiO{sub 2} layer was enhanced, which eventually helped to improve the corrosion property of the welded samples. The polarization resistance of the welded samples was increased by more than ten times compared to that of the un-welded samples. From differential scanning calorimetry (DSC), it became evident that phase transformation temperatures got changed due to welding.
Competing Interactions between Mesoscale Length-Scales, Order-Disorder, and Martensitic Transformation in Ferromagnetic Shape Memory Alloys
In the present study, the effects of composition and heat treatments and the resulting microstructural changes on the martensitic transformation and ferromagnetic transition have been investigated in NiCoMnIn metamagnetic shape memory alloys. In this shape memory alloy system, it is observed that upon heat treatments at a wide temperature range, the onset temperature of the martensitic transformation follows a non-monotonic behavior with respect to heat treatment time, and the nature of the non-monotonic behavior is also a function of composition. This behavior cannot be attributed to well-known factors such as precipitation, change in local composition due to the precipitation and/or global degree of order. In this work, a systematic investigation through synthesis, thermal processing and characterization via thermo-physical measurements, transmission electron microscopy and in-situ synchrotron x-ray diffraction experiments has been used to correlate the non-monotonic dependence of the martensitic transformation and ferromagnetic transition temperatures to the evolution of L2 1 domains arising from a order/disorder phase transition. A thermodynamic model for the magneto-structural transition is combined with classical nucleation theory to further ascertain the role of microstructural length-scales on the onset of the martensitic transformation. This work thus provides understanding of the thermodynamic and kinetic factors that can be controlled to tune the coupled magneto-structural transformations in NiCoMnIn metamagnetic shape memory alloys.
Erratum: “Total ionizing dose effect of γ-ray radiation on the switching characteristics and filament stability of HfOx resistive random access memory” [Appl. Phys. Lett. 104, 183507 (2014)]
No abstract prepared.
Application-Controlled Demand Paging for Out-of-Core Visualization
In the area of scientific visualization, input data sets are often very large. In visualization of Computational Fluid Dynamics (CFD) in particular, input data sets today can surpass 100 Gbytes, and are expected to scale with the ability of supercomputers to generate them. Some visualization tools already partition large data sets into segments, and load appropriate segments as they are needed. However, this does not remove the problem for two reasons: 1) there are data sets for which even the individual segments are too large for the largest graphics workstations, 2) many practitioners do not have access to workstations with the memory capacity required to load even a segment, especially since the state-of-the-art visualization tools tend to be developed by researchers with much more powerful machines. When the size of the data that must be accessed is larger than the size of memory, some form of virtual memory is simply required. This may be by segmentation, paging, or by paged segments. In this paper we demonstrate that complete reliance on operating system virtual memory for out-of-core visualization leads to poor performance. We then describe a paged segment system that we have implemented, and explore the principles of memory management that can be employed by the application for out-of-core visualization. We show that application control over some of these can significantly improve performance. We show that sparse traversal can be exploited by loading only those data actually required. We show also that application control over data loading can be exploited by 1) loading data from alternative storage format (in particular 3-dimensional data stored in sub-cubes), 2) controlling the page size. Both of these techniques effectively reduce the total memory required by visualization at run-time. We also describe experiments we have done on remote out-of-core visualization (when pages are read by demand from remote disk) whose results are promising.
Effect of electrode material on characteristics of non-volatile resistive memory consisting of Ag{sub 2}S nanoparticles
In this study, Ag{sub 2}S nanoparticles are synthesized and used as the active material for two-terminal resistance switching memory devices. Sintered Ag{sub 2}S films are successfully crystallized on plastic substrates with synthesized Ag{sub 2}S nanoparticles, after a relatively low-temperature sintering process (200 °C). After the sintering process, the crystallite size is increased from 6.8 nm to 80.3 nm. The high ratio of surface atoms to inner atoms of nanoparticles reduces the melting point temperature, deciding the sintering process temperature. In order to investigate the resistance switching characteristics, metal/Ag{sub 2}S/metal structures are fabricated and tested. The effect of the electrode material on the non-volatile resistive memory characteristics is studied. The bottom electrochemically inert materials, such as Au and Pt, were critical for maintaining stable memory characteristics. By using Au and Pt inert bottom electrodes, we are able to significantly improve the memory endurance and retention to more than 10{sup 3} cycles and 10{sup 4} sec, respectively.
Manipulation of magnetostructural transition and realization of prominent multifunctional magnetoresponsive properties in NiCoMnIn alloys
Promising multifunctional magnetoresponsive effects such as magnetoresistance, magnetostrain, and the magnetocaloric effect have recently been extensively studied in Ni-Mn-based metamagnetic shape memory alloys, but large reversible magnetoresponsive effects are usually obtained under high magnetic fields, which is an obstacle for practical applications. In this work, through manipulating magnetostructural transition, we achieved large reversible magnetoresponsive effects under a relatively low magnetic field of 3 T in a Ni-Co-Mn-In alloy. By systematically tuning the Mn/In ratio and Co substitution, an optimum composition Ni 49 Co 3 Mn 34 In 14 with a low thermal hysteresis (8 K), a narrow transformation interval (7 K) and a high sensitivity of transformation temperature to field change (6KT -1 ), was obtained. Good geometric compatibility between austenite and martensite was revealed by in situ synchrotron high-energy x-ray diffraction experiment, which accounts for the low hysteresis and narrow transformation interval. A reversible transformation between pure austenite and pure martensite is induced by a relatively low field of 3 T, which was directly evidenced by in situ neutron diffraction experiments. As a result, a large reversible magnetocaloric effect with entropy change of 16.5Jkg -1 K -1 , a large reversible magnetostrain of 0.26%, and a large reversible magnetoresistance of 60%, under a relatively low field of 3 T, were simultaneously achieved. These reversible magnetoresponsive effects are comparable to the maximum reversible values obtained under high fields in other Ni-Mn-based alloys, but the magnetic field we applied is much lower. This research may guide the design of metamagnetic shape memory alloys with low-field-induced magnetoresponsive properties for magnetic refrigeration, magnetic sensing, and magnetic recording applications.