Small-scale mechanical testing of materials

Small-scale mechanical testing of materials has gained prominence in the last decade or so due to the continuous miniaturization of components and devices in everyday application. This review describes the various micro-fabrication processes associated with the preparation of miniaturized specimens, geometries of test specimens and the small scale testing techniques used to determine the mechanical behaviour of materials at the length scales of a few hundred micro-meters and below. This is followed by illustrative examples in a selected class of materials. The choice of the case studies is based on the relevance of the materials used in today's world: evaluation of mechanical properties of thermal barrier coatings (TBCs), applied for enhanced high temperature protection of advanced gas turbine engine components, is essential since its failure by fracture leads to the collapse of the engine system. Si-based substrates, though brittle, are indispensible for MEMS/NEMS applications. Biological specimens, whose response to mechanical loads is important to ascertain their role in diseases and to mimic their structure for attaining high fracture toughness and impact resistance. An insight into the mechanisms behind the observed size effects in metallic systems can be exploited to achieve excellent strength at the nano-scale. A future outlook of where all this is heading is also presented.

Formulation of a mathematical approach to regional frequency analysis

Estimation of design quantiles of hydrometeorological variables at critical locations in river basins is necessary for hydrological applications. To arrive at reliable estimates for locations (sites) where no or limited records are available, various regional frequency analysis (RFA) procedures have been developed over the past five decades. The most widely used procedure is based on index-flood approach and L-moments. It assumes that values of scale and shape parameters of frequency distribution are identical across all the sites in a homogeneous region. In real-world scenario, this assumption may not be valid even if a region is statistically homogeneous. To address this issue, a novel mathematical approach is proposed. It involves (i) identification of an appropriate frequency distribution to fit the random variable being analyzed for homogeneous region, (ii) use of a proposed transformation mechanism to map observations of the variable from original space to a dimensionless space where the form of distribution does not change, and variation in values of its parameters is minimal across sites, (iii) construction of a growth curve in the dimensionless space, and (iv) mapping the curve to the original space for the target site by applying inverse transformation to arrive at required quantile(s) for the site. Effectiveness of the proposed approach (PA) in predicting quantiles for ungauged sites is demonstrated through Monte Carlo simulation experiments considering five frequency distributions that are widely used in RFA, and by case study on watersheds in conterminous United States. Results indicate that the PA outperforms methods based on index-flood approach.

In situ approach for testing the enantiopurity of chiral amines and amino alcohols by H-1 NMR

An in situ approach involving a simple mix and shake method for testing the enantiopurity of primary, secondary and tertiary chiral amines and their derivatives, chiral amino alcohols, by H-1-NMR spectroscopy is developed. The protocol involves the in situ formation of chiral ammonium borate salt from a mixture of C-2 symmetric chiral BINOL, trialkoxyborane and chiral amines. The proposed concept was demonstrated convincingly on a large number of chiral and pro-chiral amines and amino alcohols, and also aids the precise measurement of enantiomeric excess. The protocol can be completed in a couple of minutes directly in the NMR sample tube, without the need for any physical separation.

Studies on an improved indigenous pressure wave generator and its testing with a pulse tube cooler

Earlier version of an indigenously developed Pressure Wave Generator (PWG) could not develop the necessary pressure ratio to satisfactorily operate a pulse tube cooler, largely due to high blow by losses in the piston cylinder seal gap and due to a few design deficiencies. Effect of different parameters like seal gap, piston diameter, piston stroke, moving mass and the piston back volume on the performance is studied analytically. Modifications were done to the PWG based on analysis and the performance is experimentally measured. A significant improvement in PWG performance is seen as a result of the modifications. The improved PWG is tested with the same pulse tube cooler but with different inertance tube configurations. A no load temperature of 130 K is achieved with an inertance tube configuration designed using Sage software. The delivered PV power is estimated to be 28.4 W which can produce a refrigeration of about 1 W at 80 K.

Deformation field heterogeneity in punch indentation

Plastic heterogeneity in indentation is fundamental for understanding mechanics of hardness testing and impression-based deformation processing methods. The heterogeneous deformation underlying plane-strain indentation was investigated in plastic loading of copper by a flat punch. Deformation parameters were measured, in situ, by tracking the motion of asperities in high-speed optical imaging. These measurements were coupled with multi-scale analyses of strength, microstructure and crystallographic texture in the vicinity of the indentation. Self-consistency is demonstrated in description of the deformation field using the in situ mechanics-based measurements and post-mortem materials characterization. Salient features of the punch indentation process elucidated include, among others, the presence of a dead-metal zone underneath the indenter, regions of intense strain rate (e. g. slip lines) and extent of the plastic flow field. Perhaps more intriguing are the transitions between shear-type and compression-type deformation modes over the indentation region that were quantified by the high-resolution crystallographic texture measurements. The evolution of the field concomitant to the progress of indentation is discussed and primary differences between the mechanics of indentation for a rigid perfectly plastic material and a strain-hardening material are described.

Bayesian Accelerated Life Testing under Competing Weibull Causes of Failure

Consider a J-component series system which is put on Accelerated Life Test (ALT) involving K stress variables. First, a general formulation of ALT is provided for log-location-scale family of distributions. A general stress translation function of location parameter of the component log-lifetime distribution is proposed which can accommodate standard ones like Arrhenius, power-rule, log-linear model, etc., as special cases. Later, the component lives are assumed to be independent Weibull random variables with a common shape parameter. A full Bayesian methodology is then developed by letting only the scale parameters of the Weibull component lives depend on the stress variables through the general stress translation function. Priors on all the parameters, namely the stress coefficients and the Weibull shape parameter, are assumed to be log-concave and independent of each other. This assumption is to facilitate Gibbs sampling from the joint posterior. The samples thus generated from the joint posterior is then used to obtain the Bayesian point and interval estimates of the system reliability at usage condition.

Bayesian Accelerated Life Testing under Competing Weibull Causes of Failure

Consider a J-component series system which is put on Accelerated Life Test (ALT) involving K stress variables. First, a general formulation of ALT is provided for log-location-scale family of distributions. A general stress translation function of location parameter of the component log-lifetime distribution is proposed which can accommodate standard ones like Arrhenius, power-rule, log-linear model, etc., as special cases. Later, the component lives are assumed to be independent Weibull random variables with a common shape parameter. A full Bayesian methodology is then developed by letting only the scale parameters of the Weibull component lives depend on the stress variables through the general stress translation function. Priors on all the parameters, namely the stress coefficients and the Weibull shape parameter, are assumed to be log-concave and independent of each other. This assumption is to facilitate Gibbs sampling from the joint posterior. The samples thus generated from the joint posterior is then used to obtain the Bayesian point and interval estimates of the system reliability at usage condition.

Biomechanics of substrate boring by fig wasps

Female insects of diverse orders bore into substrates to deposit their eggs. Such insects must overcome several biomechanical challenges to successfully oviposit, which include the selection of suitable substrates through which the ovipositor can penetrate without itself fracturing. In many cases, the insect may also need to steer and manipulate the ovipositor within the substrate to deliver eggs at desired locations before rapidly retracting her ovipositor to avoid predation. In the case of female parasitoid ichneumonid wasps, this process is repeated multiple times during her lifetime, thus testing the ability of the ovipositioning apparatus to endure fracture and fatigue. What specific adaptations does the ovipositioning apparatus of a female ichneumonoid wasp possess to withstand these challenges? We addressed this question using a model system composed of parasitoid and pollinator fig wasps. First, we show that parasitoid ovipositor tips have teeth-like structures, preferentially enriched with zinc, unlike the smooth morphology of pollinator ovipositors. We describe sensillae present on the parasitoid ovipositor tip that are likely to aid in the detection of chemical species and mechanical deformations and sample microenvironments within the substrate. Second, using atomic force microscopy, we show that parasitoid tip regions have a higher modulus compared with regions proximal to the abdomen in parasitoid and pollinator ovipositors. Finally, we use videography to film wasps during substrate boring and analyse buckling of the ovipositor to estimate the forces required for substrate boring. Together, these results allow us to describe the biomechanical principles underlying substrate boring in parasitoid ichneumonid wasps. Such studies may be useful for the biomimetic design of surgical tools and in the use of novel mechanisms to bore through hard substrates.

Discovering Math APIs by Mining Unit Tests

In today's API-rich world, programmer productivity depends heavily on the programmer's ability to discover the required APIs. In this paper, we present a technique and tool, called MATHFINDER, to discover APIs for mathematical computations by mining unit tests of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code to compute the expression by mapping its subexpressions to API method calls. For each subexpression, MATHFINDER searches for a method such that there is a mapping between method inputs and variables of the subexpression. The subexpression, when evaluated on the test inputs of the method under this mapping, should produce results that match the method output on a large number of tests. We implemented MATHFINDER as an Eclipse plugin for discovery of third-party Java APIs and performed a user study to evaluate its effectiveness. In the study, the use of MATHFINDER resulted in a 2x improvement in programmer productivity. In 96% of the subexpressions queried for in the study, MATHFINDER retrieved the desired API methods as the top-most result. The top-most pseudo-code snippet to implement the entire expression was correct in 93% of the cases. Since the number of methods and unit tests to mine could be large in practice, we also implement MATHFINDER in a MapReduce framework and evaluate its scalability and response time.

Group Testing-Based Spectrum Hole Search for Cognitive Radios

This paper investigates the use of adaptive group testing to find a spectrum hole of a specified bandwidth in a given wideband of interest. We propose a group testing-based spectrum hole search algorithm that exploits sparsity in the primary spectral occupancy by testing a group of adjacent subbands in a single test. This is enabled by a simple and easily implementable sub-Nyquist sampling scheme for signal acquisition by the cognitive radios (CRs). The sampling scheme deliberately introduces aliasing during signal acquisition, resulting in a signal that is the sum of signals from adjacent subbands. Energy-based hypothesis tests are used to provide an occupancy decision over the group of subbands, and this forms the basis of the proposed algorithm to find contiguous spectrum holes of a specified bandwidth. We extend this framework to a multistage sensing algorithm that can be employed in a variety of spectrum sensing scenarios, including noncontiguous spectrum hole search. Furthermore, we provide the analytical means to optimize the group tests with respect to the detection thresholds, number of samples, group size, and number of stages to minimize the detection delay under a given error probability constraint. Our analysis allows one to identify the sparsity and SNR regimes where group testing can lead to significantly lower detection delays compared with a conventional bin-by-bin energy detection scheme; the latter is, in fact, a special case of the group test when the group size is set to 1 bin. We validate our analytical results via Monte Carlo simulations.

Mining Unit Tests for Discovery and Migration of Math APIs

Today's programming languages are supported by powerful third-party APIs. For a given application domain, it is common to have many competing APIs that provide similar functionality. Programmer productivity therefore depends heavily on the programmer's ability to discover suitable APIs both during an initial coding phase, as well as during software maintenance. The aim of this work is to support the discovery and migration of math APIs. Math APIs are at the heart of many application domains ranging from machine learning to scientific computations. Our approach, called MATHFINDER, combines executable specifications of mathematical computations with unit tests (operational specifications) of API methods. Given a math expression, MATHFINDER synthesizes pseudo-code comprised of API methods to compute the expression by mining unit tests of the API methods. We present a sequential version of our unit test mining algorithm and also design a more scalable data-parallel version. We perform extensive evaluation of MATHFINDER (1) for API discovery, where math algorithms are to be implemented from scratch and (2) for API migration, where client programs utilizing a math API are to be migrated to another API. We evaluated the precision and recall of MATHFINDER on a diverse collection of math expressions, culled from algorithms used in a wide range of application areas such as control systems and structural dynamics. In a user study to evaluate the productivity gains obtained by using MATHFINDER for API discovery, the programmers who used MATHFINDER finished their programming tasks twice as fast as their counterparts who used the usual techniques like web and code search, IDE code completion, and manual inspection of library documentation. For the problem of API migration, as a case study, we used MATHFINDER to migrate Weka, a popular machine learning library. Overall, our evaluation shows that MATHFINDER is easy to use, provides highly precise results across several math APIs and application domains even with a small number of unit tests per method, and scales to large collections of unit tests.

Spiral-wave dynamics in ionically realistic mathematical models for human ventricular tissue: the effects of periodic deformation

We carry out an extensive numerical study of the dynamics of spiral waves of electrical activation, in the presence of periodic deformation (PD) in two-dimensional simulation domains, in the biophysically realistic mathematical models of human ventricular tissue due to (a) ten-Tusscher and Panfilov (the TP06 model) and (b) ten-Tusscher, Noble, Noble, and Panfilov (the TNNPO4 model). We first consider simulations in cable-type domains, in which we calculate the conduction velocity theta and the wavelength lambda of a plane wave; we show that PD leads to a periodic, spatial modulation of theta and a temporally periodic modulation of lambda; both these modulations depend on the amplitude and frequency of the PD. We then examine three types of initial conditions for both TP06 and TNNPO4 models and show that the imposition of PD leads to a rich variety of spatiotemporal patterns in the transmembrane potential including states with a single rotating spiral (RS) wave, a spiral-turbulence (ST) state with a single meandering spiral, an ST state with multiple broken spirals, and a state SA in which all spirals are absorbed at the boundaries of our simulation domain. We find, for both TP06 and TNNPO4 models, that spiral-wave dynamics depends sensitively on the amplitude and frequency of PD and the initial condition. We examine how these different types of spiral-wave states can be eliminated in the presence of PD by the application of low-amplitude pulses by square- and rectangular-mesh suppression techniques. We suggest specific experiments that can test the results of our simulations.