Implementation of customer relationship management and inventory control software: a multiple case study of small retailers

Gemstone Team Small Business Solutions

The Impact of Worsening Heart Failure in the United States.

In-hospital worsening heart failure represents a clinical scenario wherein a patient hospitalized for acute heart failure experiences a worsening of their condition, requiring escalation of therapy. Worsening heart failure is associated with worse in-hospital and postdischarge outcomes. Worsening heart failure is increasingly being used as an endpoint or combined endpoint in clinical trials, as it is unique to episodes of acute heart failure and captures an important event during the inpatient course. While prediction models have been developed to identify worsening heart failure, there are no known FDA-approved medications associated with decreased worsening heart failure. Continued study is warranted.

The numerical simulation of noncharring thermal degradation and its application to the prediction of compartment fire development

In this paper we present some work concerned with the development and testing of a simple solid fuel combustion model incorporated within a Computational Fluid Dynamics (CFD) framework. The model is intended for use in engineering applications of fire field modeling and represents an extension of this technique to situations involving the combustion of solid fuels. The CFD model is coupled with a simple thermal pyrolysis model for combustible solid noncharring fuels, a six-flux radiation model and an eddy-dissipation model for gaseous combustion. The model is then used to simulate a series of small-scale room fire experiments in which the target solid fuel is polymethylmethacrylate. The numerical predictions produced by this coupled model are found to be in very good agreement with experimental data. Furthermore, numerical predictions of the relationship between the air entrained into the fire compartment and the ventilation factor produce a characteristic linear correlation with constant of proportionality 0.38 kg/sm5/12. The simulation results also suggest that the model is capable of predicting the onset of "flashover" type behavior within the fire compartment.

A computational model for defect prediction in shape castings based on the interaction of free surface flow, heat transfer, and solidification phenomena

High-integrity castings require sophisticated design and manufacturing procedures to ensure they are essentially macrodefect free. Unfortunately, an important class of such defects—macroporosity, misruns, and pipe shrinkage—are all functions of the interactions of free surface flow, heat transfer, and solidication in complex geometries. Because these defects arise as an interaction of the preceding continuum phenomena, genuinely predictive models of these defects must represent these interactions explicitly. This work describes an attempt to model the formation of macrodefects explicitly as a function of the interacting continuum phenomena in arbitrarily complex three-dimensional geometries. The computational approach exploits a compatible set of finite volume procedures extended to unstructured meshes. The implementation of the model is described together with its testing and a measure of validation. The model demonstrates the potential to predict reliably shrinkage macroporosity, misruns, and pipe shrinkage directly as a result of interactions among free-surface fluid flow, heat transfer, and solidification.

Use of a coupled mechanical-acoustic computational model to identify failure mechanisms in paper production

In this paper, a couple mechanical-acoustic system of equations is solved to determine the relationship between emitted sound and damage mechanisims in paper under controlled stress conditions. The simple classical expression describing the frequency of a plucked string to its material properties is used to generate a numberical representation of the microscopic structue of the paper, and the resulting numerical model is then used to simulate the vibration of a range of simple fibre structures when undergoing two distinct types of damange mechanisms: (a)fibre/fibre bond failure, (b) fibre failure. The numercial results are analysed to determine whether there is any detectable systematic difference between the resulting acoustic emissions of the two damage processes. Fourier techniques are then used to compare th computeed results against experimental measurements. Distinct frequency components identifying each type of damage are shown to exist, and in this respect theory and experiments show good correspondece. Hence, it is shown, that althrough the mathematical model represents a grossly-simplified view of the complex structure of the paper, it nevertheless provides a good understanding of the underlying micro-mechanisms characterising its proeperties as a stress-resisting structure. Use of the model and acoompanying software will enable operators to identify approaching failure conditions in the continuous production of paper from emitted sound signals and take preventative action.

Integrated reliability and prognostics prediction methodology for power electronic modules

The article consists of a PowerPoint presentation on integrated reliability and prognostics prediction methodology for power electronic modules. The areas discussed include: power electronics flagship; design for reliability; IGBT module; design for manufacture; power module components; reliability prediction techniques; failure based reliability; etc.

Software Products for Modelling and Simulation in Materials Science

Models and software products have been developed for modelling, simulation and prediction of different correlations in materials science, including 1. the correlation between processing parameters and properties in titanium alloys and ?-titanium aluminides; 2. time–temperature–transformation (TTT) diagrams for titanium alloys; 3. corrosion resistance of titanium alloys; 4. surface hardness and microhardness profile of nitrocarburised layers; 5. fatigue stress life (S–N) diagrams for Ti–6Al–4V alloys. The programs are based on trained artificial neural networks. For each particular case appropriate combination of inputs and outputs is chosen. Very good performances of the models are achieved. Graphical user interfaces (GUI) are created for easy use of the models. In addition interactive text versions are developed. The models designed are combined and integrated in software package that is built up on a modular fashion. The software products are available in versions for different platforms including Windows 95/98/2000/NT, UNIX and Apple Macintosh. Description of the software products is given, to demonstrate that they are convenient and powerful tools for practical applications in solving various problems in materials science. Examples for optimisation of the alloy compositions, processing parameters and working conditions are illustrated. An option for use of the software in materials selection procedure is described.

Low pressure carbon dioxide solubility in pure electrolyte solvents for lithium-ion batteries as a function of temperature. Measurement and prediction

Experimental values for the carbon dioxide solubility in eight pure electrolyte solvents for lithium ion batteries – such as ethylene carbonate (EC), propylene carbonate (PC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC), ?-butyrolactone (?BL), ethyl acetate (EA) and methyl propionate (MP) – are reported as a function of temperature from (283 to 353) K and atmospheric pressure. Based on experimental solubility data, the Henry’s law constant of the carbon dioxide in these solvents was then deduced and compared with reported values from the literature, as well as with those predicted by using COSMO-RS methodology within COSMOthermX software and those calculated by the Peng–Robinson equation of state implemented into Aspen plus. From this work, it appears that the CO2 solubility is higher in linear carbonates (such as DMC, EMC, DEC) than in cyclic ones (EC, PC, ?BL). Furthermore, the highest CO2 solubility was obtained in MP and EA solvents, which are comparable to the solubility values reported in classical ionicliquids. The precision and accuracy of the experimental values, considered as the per cent of the relative average absolute deviations of the Henry’s law constants from appropriate smoothing equations and from literature values, are close to (1% and 15%), respectively. From the variation of the Henry’s law constants with temperature, the partial molar thermodynamic functions of dissolution such as the standard Gibbs free energy, the enthalpy, and the entropy are calculated, as well as the mixing enthalpy of the solvent with CO2 in its hypothetical liquid state.

Towards an understanding of the causes and effects of software requirements change: two case studies

Changes to software requirements not only pose a risk to the successful delivery of software applications but also provide opportunity for improved usability and value. Increased understanding of the causes and consequences of change can support requirements management and also make progress towards the goal of change anticipation. This paper presents the results of two case studies that address objectives arising from that ultimate goal. The first case study evaluated the potential of a change source taxonomy containing the elements ‘market’, ‘organisation’, ‘vision’, ‘specification’, and ‘solution’ to provide a meaningful basis for change classification and measurement. The second case study investigated whether the requirements attributes of novelty, complexity, and dependency correlated with requirements volatility. While insufficiency of data in the first case study precluded an investigation of changes arising due to the change source of ‘market’, for the remainder of the change sources, results indicate a significant difference in cost, value to the customer and management considerations. Findings show that higher cost and value changes arose more often from ‘organisation’ and ‘vision’ sources; these changes also generally involved the co-operation of more stakeholder groups and were considered to be less controllable than changes arising from the ‘specification’ or ‘solution’ sources. Results from the second case study indicate that only ‘requirements dependency’ is consistently correlated with volatility and that changes coming from each change source affect different groups of requirements. We conclude that the taxonomy can provide a meaningful means of change classification, but that a single requirement attribute is insufficient for change prediction. A theoretical causal account of requirements change is drawn from the implications of the combined results of the two case studies.

A probabilistic modelling scheme for analysis of long-term failure of cemented femoral joint replacements

Reliable prediction of long-term medical device performance using computer simulation requires consideration of variability in surgical procedure, as well as patient-specific factors. However, even deterministic simulation of long-term failure processes for such devices is time and resource consuming so that including variability can lead to excessive time to achieve useful predictions. This study investigates the use of an accelerated probabilistic framework for predicting the likely performance envelope of a device and applies it to femoral prosthesis loosening in cemented hip arthroplasty.
A creep and fatigue damage failure model for bone cement, in conjunction with an interfacial fatigue model for the implant–cement interface, was used to simulate loosening of a prosthesis within a cement mantle. A deterministic set of trial simulations was used to account for variability of a set of surgical and patient factors, and a response surface method was used to perform and accelerate a Monte Carlo simulation to achieve an estimate of the likely range of prosthesis loosening. The proposed framework was used to conceptually investigate the influence of prosthesis selection and surgical placement on prosthesis migration.
Results demonstrate that the response surface method is capable of dramatically reducing the time to achieve convergence in mean and variance of predicted response variables. A critical requirement for realistic predictions is the size and quality of the initial training dataset used to generate the response surface and further work is required to determine the recommendations for a minimum number of initial trials. Results of this conceptual application predicted that loosening was sensitive to the implant size and femoral width. Furthermore, different rankings of implant performance were predicted when only individual simulations (e.g. an average condition) were used to rank implants, compared with when stochastic simulations were used. In conclusion, the proposed framework provides a viable approach to predicting realistic ranges of loosening behaviour for orthopaedic implants in reduced timeframes compared with conventional Monte Carlo simulations.

Low pressure carbon dioxide solubility in lithium-ion batteries based electrolytes as a function of temperature. Measurement and prediction

We present in this study the effect of nature and concentration of lithium salt, such as the lithium hexafluorophosphate, LiPF6; lithium tris(pentafluoroethane)-trifluorurophosphate LiFAP; lithium bis(trifluoromethylsulfonyl)imide, LiTFSI, on the CO2 solubility in four electrolytes for lithium ion batteries based on pure solvent that include ethylene carbonate (EC), dimethyl carbonate (DMC), ethyl methyl carbonate (EMC), diethyl carbonate (DEC), as well as, in the EC:DMC, EC:EMC and EC:DEC (50:50) wt.% binary mixtures as a function of temperature from (283 to 353) K and atmospheric pressure. Based on experimental solubility values, the Henry’s law constant of the carbon dioxide in these solutions with the presence or absence of lithium salt was then deduced and compared with reported values from the literature, as well as with those predicted by using COSMO-RS methodology within COSMOThermX software. From this study, it appears that the addition of 1 mol · dm-3 LiPF6 salt in alkylcarbonate solvents decreases their CO2 capture capacity. By using the same experimental conditions, an opposite CO2 solubility trend was generally observed in the case of the addition of LiFAP or LiTFSI salts in these solutions. Additionally, in all solutions investigated during this work, the CO2 solubility is greater in electrolytes containing the LiFAP salt, followed by those based on the LiTFSI case. The precision and accuracy of the experimental data reported therein, which are close to (1 and 15)%, respectively. From the variation of the Henry’s law constant with temperature, the partial molar thermodynamic functions of dissolution such as the standard Gibbs energy, the enthalpy, and the entropy, as well as the mixing enthalpy of the solvent with CO2 in its hypothetical liquid state were calculated. Finally, a quantitative analysis of the CO2 solubility evolution was carried out in the EC:DMC (50:50) wt.% binary mixture as the function of the LiPF6 or LiTFSI concentration in solution to elucidate how ionic species modify the CO2 solubility in alkylcarbonates-based Li-ion electrolytes by investigating the salting effects at T = 298.15 K and atmospheric pressure.