This paper evaluates a Successive Response Surface Method (SRSM) specifically developed for simulation-based design optimization, e.g. that of explicit nonlinear dynamics in crashworthiness design. Linear response surfaces are constructed in a subregion of the design space using a design of experiments approach with a D-optimal experimental design. To converge to an optimum, a domain reduction scheme is utilized. The scheme requires only one user-defined parameter, namely the size of the initial subregion. During optimization, the size of this region is adapted using a move reversal criterion to counter oscillation and a move distance criterion to gauge accuracy. To test its robustness, the results using the method are compared to SQP results of a selection of the well-known Hock and Schittkowski problems. Although convergence to a small tolerance is slow when compared to SQP, the SRSM method does remarkably well for these sometimes pathological analytical problems. The second test concerns three engineering problems sampled from the nonlinear structural dynamics field to investigate the method's handling of numerical noise and non-linearity. It is shown that, despite its simplicity, the SRSM method converges stably and is relatively insensitive to its only user-required input parameter.

To increase the efficiency of Concentrated Solar Power (CSP) plants, the use of optimization methods is a current topic of research. This paper focuses on applying an integrated optimization technology to a solar thermal application, more specifically for the optimization of a trapezoidal cavity absorber of an LFR (Linear Fresnel Reflector), also called a Linear Fresnel Collector (LFC), CSP plant. LFR technology has been developed since the 1960s, and while large improvements in efficiencies have been made, there is still room for improvement. Once such area is in the receiver design where the optimal cavity shape, coatings, insulation thickness, absorber pipe selection, layout and spacing always need to be determined for a specific application. This paper uses a commercial tool to find an optimal design for a set of operating conditions. The objective functions that are used to judge the performance of a 2-D cavity are the combined heat loss through convection, conduction and radiation, as well as a wind resistance area. In this paper the effect of absorbed irradiation is introduced in the form of an outer surface of pipe temperature. Seven geometrical parameters are used as design variables. Based on a sample set requiring 79 CFD simulations, a global utopia point is found that minimizes both objectives. The most sensitive parameters were found to be the top insulation thickness and the cavity depth. Based on the results, the Multi-Objective Genetic Algorithm (MOGA) as contained in ANSYS DesignXplorer is shown to be effective in finding candidate optimal designs as well as the utopia point.

A computational approach is presented, which uses the finite volume (FV) method in the Computational Fluid Dynamics (CFD) solver ANSYS Fluent to conduct the ray tracing required to quantify the optical performance of a line concentration Concentrated Solar Power (CSP) receiver, as well as the conjugate heat transfer modelling required to estimate the thermal efficiency of such a receiver. A Linear Fresnel Collector (LFC) implementation is used to illustrate the approach. It is shown that the Discrete Ordinates method can provide an accurate solution to the Radiative Transfer Equation (RTE) if the shortcomings of its solution are resolved appropriately in the FV CFD solver. The shortcomings are due to false scattering and the socalled ray effect inherent in the FV solution. The approach is first evaluated for a 2-D test case involving oblique collimated radiation and then for a more complex 2-D LFC optical domain based on the FRESDEMO project. For the latter, results are compared with and validated against those obtained with the Monte Carlo ray tracer, SolTrace. The outcome of the FV ray tracing in the LFC optical domain is mapped as a non-uniform heat flux distribution in the 3-D cavity receiver domain and this distribution is included in the FV conjugate heat transfer CFD model as a volumetric source. The result of this latter model is the determination of the heat transferred to the heat transfer fluid running in the collector tubes, thereby providing an estimation of the overall thermal efficiency. To evaluate the effectiveness of the phased approach in terms of accuracy and computational cost, the novel 2-D:3-D phased approach is compared with results of a fully integrated, but expensive 3-D optical and thermal model. It is shown that the less expensive model provides similar results and hence a large cost saving. The novel approach also provides the benefit of working in one simulation environment, i.e. ANSYS Workbench, where optimisation studies can be carried out to maximise the performance of linear CSP reflector layout and receiver configurations.

Plume injection height influences plume transport characteristics, such as range and potential for dilution. We evaluated plume injection height from a predictive wildland fire smoke transport model over the contiguous United States (U.S.) from 2006 to 2008 using satellite-derived information, including plume top heights from the Multi-angle Imaging SpectroRadiometer (MISR) Plume Height Climatology Project and aerosol vertical profiles from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). While significant geographic variability was found in the comparison between modeled plumes and satellite-detected plumes, modeled plume heights were lower overall. In the eastern U.S., satellite-detected and modeled plume heights were similar (median height 671 and 660 m respectively). Both satellite-derived and modeled plume injection heights were higher in the western U.S. (2345 and 1172 m, respectively). Comparisons of modeled plume injection height to satellite-derived plume height at the fire location (R2 = 0.1) were generally worse than comparisons done downwind of the fire (R2 = 0.22). This suggests that the exact injection height is not as important as placement of the plume in the correct transport layer for transport modeling

[1] We evaluated predictions of hourly PM 2.5 surface concentrations produced by the experimental BlueSky Gateway air quality modeling system during two wildfire episodes in southern California (Case 1) and northern California (Case 2). In southern California, the prediction performance was dominated by the prevailing synoptic weather patterns, which differentiated the smoke plumes into two types: narrow and highly concentrated during an offshore flow, and diluted and well-mixed during a light onshore flow. For the northern California fires, the prediction performance was dominated by terrain and the limitations of predicting concentrations in a narrow valley, rather than by the synoptic pattern, which did not differ much throughout the wildfire episode. There was an over-prediction bias for the maximum values during this episode. When the predicted values were compared to observed values, the best performance results were for the onshore flow during the southern California fires, indicating that the coarse grid used by BlueSky Gateway appropriately represented these well-mixed conditions. Overall, the southern California fire predictions were biased low and the model did not reproduce the high hourly concentrations (>240 mg/m 3 ) observed by the monitors. The predicted results performed well against the observations for the northern California fires, with a large number of predicted values within acceptable range of the observed values.Citation: Strand, T.

Purpose -The purpose of this paper is to provide a methodology with which to perform variable screening and optimization in automotive crashworthiness design. Design/methodology/approach -The screening method is based on response surface methodology in which linear response surfaces are used to create approximations to the design response. The response surfaces are used to estimate the sensitivities of the responses with respect to the design variables while the variance is used to estimate the confidence interval of the regression coefficients. The sampling is based on the D-optimality criterion with over-sampling to improve noise filtering and find the best estimate of the regression coefficients. The coefficients and their confidence intervals as determined using analysis of variance (ANOVA), are used to construct bar charts for the purpose of selecting the important variables. Findings -A known analytical function is first used to illustrate the effectiveness of screening. Using the finite element method (FEM), a complex vehicle occupant impact problem and a full vehicle multidisciplinary problem featuring frontal impact and torsional modal analysis of the vehicle body are modeled and parameterized. Two optimizations are conducted for each FEM example, one with the full variable set and one with a screened subset. An iterative, successive linear approximation method is used to achieve convergence. It is shown that, although significantly different final designs may be

A computational fluid dynamics (CFD) model that evaluates mechanical mixing in a full-scale anaerobic digester was developed to investigate the influence of sewage sludge rheology on the steady-state digester performance. Mechanical mixing is provided through an impeller located in a draft tube. Use is made of the Multiple Reference Frame model to incorporate the rotating impeller.The non-Newtonian sludge is modeled using the Hershel-Bulkley law because of the yield stress present in the fluid. Water is also used as modeling fluid to illustrate the significant non-Newtonian effects of sewage sludge on mixing patterns. The variation of the sewage sludge rheology as a result of the digestion process is considered to determine its influence on both the required impeller torque and digester mixing patterns. It was found that when modeling the fluid with the HershelBulkley law, the high slope of the sewage stress-strain curve at high shear rates causes significant viscous torque on the impeller surface. Although the overall fluid shear stress property is reduced during digestion, this slope is increased with sludge age, causing an increase in impeller torque for digested sludge due to the high strain rates caused by the pumping impeller. Consideration should be given to using the Bingham law to deal with high strain rates. The overall mixing flow patterns of the digested sludge do however improve slightly.

To elucidate the relationship between factors resolved by the positive matrix factorization (PMF) receptor model and actual emission sources and to refine the PMF modeling strategy, speciated PM 2.5 (particulate matter with aerodynamic diameter Ͻ2.5 m) data generated from a state-of-the-art chemical transport model for two rural sites in the eastern United States are subjected to PMF analysis. In addition to 2 and R 2 used to infer the quality of fitting, the interpretability of PMF factors with respect to known primary and secondary sources is evaluated using a root mean square difference analysis. For the most part, factors are found to represent imperfect combinations of sources, and the optimal number of factors should be just adequate to explain the input data (e.g., R 2 Ͼ 0.95). Retaining more factors in the model does not help resolve minor sources, unless temporal resolution of the data is increased, thus allowing more information to be used by the model. If guided with a priori knowledge of source markers and/or special events, rotation of factors leads to more interpretable PMF factors. The choice of uncertainty weighting coefficients greatly influences the PMF modeling results, but it cannot usually be determined for simulated or real-world data. A simple test is recommended to check whether the weighting coefficients are suitable. However, uncertainties in the data divert PMF solutions even when the optimal weighting coefficients and number of factors are in place.