Design of particle-reinforced polyurethane mould materials for soft tooling process using evolutionary multi-objective optimization algorithms

Polyurethane is used for making mould in soft tooling (ST) process for producing wax/plastic components. These wax components are later used as pattern in investment casting process. Due to low thermal conductivity of polyurethane, cooling time in ST process is long. To reduce the cooling time, thermal conductive fillers are incorporated into polyurethane to make composite mould material. However, addition of fillers affects various properties of the ST process, such as stiffness of the mould box, rendering flow-ability of melt mould material, etc. In the present work, multi-objective optimization of various conflicting objectives (namely maximization of equivalent thermal conductivity, minimization of effective modulus of elasticity, and minimization of equivalent viscosity) of composite material are conducted using evolutionary algorithms (EAs) in order to design particle-reinforced polyurethane composites by finding the optimal values of design parameters. The design parameters include volume fraction of filler content, size and shape factor of filler particle, etc. The Pareto-optimal front is targeted by solving the corresponding multi-objective problem using the NSGA-II procedure. Then, suitable multi-criterion decision-making techniques are employed to select one or a small set of the optimal solution(s) of design parameter(s) based on the higher level information of the ST process for industrial applications. Finally, the experimental study with a typical real industrial application demonstrates that the obtained optimal design parameters significantly reduce the cooling time in soft tooling process keeping other processing advantages.     

Collapsing and Separating Completeness Notions Under Average-Case and Worst-Case Hypotheses

This paper presents the following results on sets that are complete for NP.

1. If there is a problem in NP that requires $2^{n^{\Omega(1)}}$ time at almost all lengths, then every many-one NP-complete set is complete under length-increasing reductions that are computed by polynomial-size circuits.
2. If there is a problem in co-NP that cannot be solved by polynomial-size nondeterministic circuits, then every many-one NP-complete set is complete under length-increasing reductions that are computed by polynomial-size circuits.
3. If there exist a one-way permutation that is secure against subexponential-size circuits and there is a hard tally language in NP??co-NP, then there is a Turing complete language for NP that is not many-one complete.

Our first two results use worst-case hardness hypotheses whereas earlier work that showed similar results relied on average-case or almost-everywhere hardness assumptions. The use of average-case and worst-case hypotheses in the last result is unique as previous results obtaining the same consequence relied on almost-everywhere hardness results.     

BFO optimized RLS algorithm for power system harmonics estimation

In this paper a new estimation approach combining both Recursive Least Square (RLS) and Bacterial Foraging Optimization (BFO) is developed for accurate estimation of harmonics in distorted power system signals. The proposed RLS–BFO hybrid technique has been employed for estimating the fundamental as well as harmonic components present in power system voltage/current waveforms. The basic foraging strategy is made adaptive by using RLS that sequentially updates the unknown parameters of the signal. Simulation and experimental studies are included justifying the improvement in performance of this new estimation algorithm.     

Measurements and analysis of transmitted spectra from LOTUS fission-suppressed hybrid blanket driven by D-T neutrons

The neutron spectra transmitted across a fission-suppressed hybrid blanket and its components, driven by a low intensity 14 MeV Haefely neutron generator, were measured with a 2×2 NE213 detector at LOTUS facility. These experiments have been analyzed with 2D and 3D codes DOT3.5 and MCNP, respectively. The spectral integrals between 15 to 1 MeV show good agreement among the 2D, the 3D, and the NE213 for 15 cm lead, 18 cm beryllium, and 25 cm graphite slabs. However, there are large discrepancies for 6.2 cm stainless steel and 15 cm lithium carbonate slabs. The assemblies involving two or more of these slabs reflect these tendencies. We observe also considerable disagreement over pointwise spectra for a number of assemblies.Work done while on visiting assignment to Institut de Génie Atomique, E.P.F.L.     

Welding of thin steel plates: a new model for thermal analysis

A mathematical model for the transient heat flow analysis in arc-welding processes is proposed, based on a unique set of boundary conditions. The model attempts to make use of the relative advantages of analytical as well as numerical techniques in order to reduce the problem size for providing a quicker solution without sacrificing the accuracy of prediction. The variation of thermo-physical properties with temperature has been incorporated into the model to improve the thermal analysis in the weld and heat-affected zones. The model has been evaluated using a five-point explicit finite difference method for analysing the welding heat flow in thin plates of two different geometric configurations. The temperature distribution closer to the heat source, primarily in the weld zone and the heat-affected zones, are predicted by the numerical technique. The thermal characteristics beyond the heat-affected zone are amenable to standard analytical techniques. The behaviour of the boundary condition in the model has been investigated in detail.Nomenclature q Rate of heat per unit thickness (Wm^–1) - d Plate thickness (m) - v Velocity of source (m s^–1) - t Time (s) - T Temperature value at the desired point (K) - T ₀ Initial temperature (K) - K Thermal conductivity (W m^–1 K^–1) - Density (kg m^–3) - c _p Specific heat (J kg^–1 K^–1) - Thermal diffusivity (m² s^–1) - n - Distance of point considered from the source (=x–vt) (m) - K ₀ Modified Bessel function of second kind and zero order - r Radial distance from the source (r=(x ²+y ²)^1/2) (m) - Model width (m) - a Plate width (m) - Distance from the source =(²+4 ×10^–4)^1/2 (m) - _n      

Parallel depth first search. Part II. Analysis

This paper presents the analysis of a parallel formulation of depth-first search. At the heart of this parallel formulation is a dynamic work-distribution scheme that divides the work between different processors. The effectiveness of the parallel formulation is strongly influenced by the work-distribution scheme and the target architecture. We introduce the concept of isoefficiency function to characterize the effectiveness of different architectures and work-distribution schemes. Many researchers considered the ring architecture to be quite suitable for parallel depth-first search. Our analytical and experimental results show that hypercube and shared-memory architectures are significantly better. The analysis of previously known work-distribution schemes motivated the design of substantially improved schemes for ring and shared-memory architectures. In particular, we present a work-distribution algorithm that guarantees close to optimal performance on a shared-memory/-network-with-message-combining architecture (e.g. RP3). Much of the analysis presented in this paper is applicable to other parallel algorithms in which work is dynamically shared between different processors (e.g., parallel divide-and-conquer algorithms). The concept of isoefficiency is useful in characterizing the scalability of a variety of parallel algorithms.This work was supported by Army Research Office Grant No. DAAG29-84-K-0060 to the Artificial Intelligence Laboratory, and Office of Naval Research Grant N00014-86-K-0763 to the Computer Science Department at the University of Texas at Austin.     

Extensive Study of Underlap Length Effect for 3-D SOI FinFET to Achieve High Switching Ratio and Low Power

Silicon - The primary purpose of this work is to study the effect of symmetric and asymmetric variation of underlap regions both on source and drain side of 3D SOI n-FinFET. Underlap length is...     

Simulation Study of Dielectric Modulated Dual Material Gate TFET Based Biosensor by Considering Ambipolar Conduction

Silicon - In this paper, a dielectric modulated dual material gate TFET (DM-DMG_TFET)based biosensor is proposed. In order to detect various biomolecules, a nanogap cavity is formed by the...     

The design,analysis, and cost estimation of a generic adder and subtractor using the layered T (LT) logic reduction methodology with a quantum-dot cellular-automata-based approach

The quantum-dot cellular automata (QCA) is considered to be one of the ground-breaking nanotechnologies developed over the last two decades. A layered T (LT) logic cell library is constructed herein, and the methodology is extended to generic adder and subtractor module designs. The two proposed algorithms lead to more efficient QCA layout designs for an n-bit ripple carry adder (RCA) and subtractor based on an effective clock zone assignment approach. The suggested one-, four-, and eight-bit RCAs and subtractors surpass most of their existing counterparts by offering lower effective area and cell complexity. A comparative analysis is presented regarding the complexity, irreversible power dissipation, and Cost_α of the proposed n-bit layouts from a cost estimation purview.

     

A Novel High Nitrogen Steel Powder Designed for Minimized Cr2N Precipitations

High nitrogen steels provide excellent mechanical properties and corrosion resistance but are prone to form precipitates which adversely affect the corrosion resistance and toughness. High nitrogen steel powders currently available in the market are not claimed to be precipitate free. It is critical to avoid these precipitates while retaining nitrogen in the dissolved form to realize the value of these powder alloys. However, retaining high level of dissolved nitrogen in steel powder during melt atomization process is very challenging. Instead, solid-state dissolution of nitrogen into the powder alloy followed by rapid cooling may provide a convenient approach to avoid precipitate formation compared to traditional melt processing. This study presents a solution treatment approach to achieve elevated dissolved nitrogen levels (~ 0.4 wt pct) in Fe–Mn–Cr powder alloy with negligible precipitation of nitrides. The influence of starting material, holding time, temperature and cooling rate on the resulting microstructure is presented. A fully austenite matrix with high dissolved nitrogen content resulted in powders with desired mechanical properties.