Wheel Topology Research Articles

Generative Design by Reinforcement Learning: Enhancing the Diversity of Topology Optimization Designs

Generative design refers to computational design methods that can automatically conduct design exploration under constraints defined by designers. Among many approaches, topology optimization-based generative designs aim to explore diverse topology designs, which cannot be represented by conventional parametric design approaches. Recently, data-driven topology optimization research has started to exploit artificial intelligence, such as deep learning or machine learning, to improve the capability of design exploration. This study proposes a reinforcement learning (RL) based generative design process, with reward functions maximizing the diversity of topology designs. We formulate generative design as a sequential problem of finding optimal design parameter combinations in accordance with a given reference design. Proximal Policy Optimization is used as the learning framework, which is demonstrated in the case study of an automotive wheel design problem. To reduce the heavy computational burden of the wheel topology optimization process required by our RL formulation, we approximate the optimization process with neural networks. With efficient data preprocessing/augmentation and neural architecture, the neural networks achieve a generalized performance and symmetricity-reserving characteristics. We show that RL-based generative design produces a large number of diverse designs within a short inference time by exploiting GPU in a fully automated manner. It is different from the previous approach using CPU which takes much more processing time and involving human intervention.

The Kahn degenerate frustration points and the Lieb-Mattis level order in heterometallic wheel molecules with competing interactions

Abstract The energy structure of heterometallic molecules with wheel topology is considered within the quantum Heisenberg spin model, using mostly the algebraic methods. In our approach, the central spin is coupled to the peripheral ones by the interaction parameter J ′ , whereas the latter located at the perimeter are subjects to the nearest-neighbour interaction J. The systems are frustrated in the regime J > 0 irrespective of the sign of J ′ and the ground state total spin quantum numbers form a universal sequence consisting of a definite number of steps as a function of the ratio α = J ′ / J . The Kahn degenerate frustration points occur at the discontinuous jumps or special symmetry junctures. In addition, the Lieb-Mattis level order is revealed despite the lack of bipartiteness, and existence of broad plateaus in the magnetisation profiles is also indicated.

Improved genetic algorithm based on particle swarm optimization-inspired reference point placement

ABSTRACTThis article investigates the use of optimal reference point placement to improve performance of non-dominated sorting genetic algorithm (NSGA). Placement of reference points for many-objective optimization is inspired by wheel and Von Neumann topologies of Particle Swarm Optimization (PSO). Results obtained show that the pattern of reference point placement determines performance efficiency of NSGA. The better-performing wheel topology (called wheel reference point genetic algorithm (wRPGA), is compared to three other many-objective evolutionary algorithms: knee-driven evolutionary algorithm (KnEA), non-dominated sorting genetic algorithm III (NSGAIII) and multi-objective evolutionary algorithm based on dominance and decomposition (MOEAD/D). The selected many-objective benchmark problems are Walking Fish Group 2 (WFG2) and Deb-Thiele-Laumanns-Zitzler 2 (DTLZ2). It is also tested on a 3-objective cost function for a hypothetical model of a stand-alone microgrid. Through the simulations, the wheel configuration performed 88.9% better than the Von Neumann configuration. The wheel topology also achieved better performance with respect to inverted generational distance (IGD) compared to KnEA, NSGAIII and MOEAD/D for 7 out of 15 IEEE Congress on Evolutionary Computation (CEC) 2017 benchmark problems. wRPGA gave a good approximation of the Pareto front for the 3-objective model representing the hypothetical microgrid.

Laser dressing of grinding wheels - a review

Grinding is one of the commonly used surface-finishing operations in the manufacturing industries to produce surfaces with close tolerances, high precision, and high quality. Selection of appropriate dressing technique with optimised dressing conditions can result in effectively opening up of the cutting edges of the abrasive grits. Several experimental investigations have hailed the laser dressing to be prosperous in generating improved grinding wheel topology that results enhanced grindability. This paper presents a comprehensive review on the developments and advances of the novel laser dressing techniques, starting from a brief introduction of basic concept, material removal mechanism, experimental arrangements, and advantages over mechanical dressing techniques. The progress in diverse laser dressing, focusing on material aspects, is thoroughly reviewed and discussed.

Laser dressing of grinding wheels A review

Grinding is one of the commonly used surface-finishing operations in the manufacturing industries to produce surfaces with close tolerances, high precision, and high quality. Selection of appropriate dressing technique with optimised dressing conditions can result in effectively opening up of the cutting edges of the abrasive grits. Several experimental investigations have hailed the laser dressing to be prosperous in generating improved grinding wheel topology that results enhanced grindability. This paper presents a comprehensive review on the developments and advances of the novel laser dressing techniques, starting from a brief introduction of basic concept, material removal mechanism, experimental arrangements, and advantages over mechanical dressing techniques. The progress in diverse laser dressing, focusing on material aspects, is thoroughly reviewed and discussed.

Grinding performance of textured monolayer CBN wheels: Undeformed chip thickness nonuniformity modeling and ground surface topography prediction

Abstract The ground surface roughness and topography are commonly used to characterize the surface finishing. In the application of textured monolayer CBN wheels, the nonuniformity of wheel topology will render a nonuniform undeformed chip thickness which greatly affects the ground surface. In order to predict the ground surface topography more accurately and efficiently, grinding experiment has been conducted in the current study, with measured grinding wheel topology. The measured surface topology of textured monolayer CBN wheels has been reconstructed by using the Johnson transformation and its inverse transformation. The influence of wheel topology evolution on the undeformed chip thickness nonuniformity has been determined with an improved model. It has been found the ground surface roughness is improved with a continuous reducing undeformed chip thickness nonuniformity. The percentage of active grains, the mean value and standard deviation of undeformed chip thickness have been found the main factors in determining the surface roughness. The reconstructed wheel surface topology has been used to predict the workpiece topography in different stages of the grinding process.

Decoherence of a single spin coupled to an interacting spin bath

Decoherence of a central spin coupled to an interacting spin bath via inhomogeneous Heisenberg coupling is studied by two different approaches, namely an exact equations of motion (EOMs) method and a Chebyshev expansion technique (CET). By assuming a wheel topology of the bath spins with uniform nearest-neighbor $XX$-type intrabath coupling, we examine the central spin dynamics with the bath prepared in two different types of bath initial conditions. For fully polarized baths in strong magnetic fields, the polarization dynamics of the central spin exhibits a collapse-revival behavior in the intermediate-time regime. Under an antiferromagnetic bath initial condition, the two methods give excellently consistent central spin decoherence dynamics for finite-size baths of $N\leq14$ bath spins. The decoherence factor is found to drop off abruptly on a short time scale and approach a finite plateau value which depends on the intrabath coupling strength non-monotonically. In the ultrastrong intrabath coupling regime, the plateau values show an oscillatory behavior depending on whether $N/2$ is even or odd. The observed results are interpreted qualitatively within the framework of the EOM and perturbation analysis. The effects of anisotropic spin-bath coupling and inhomogeneous intrabath bath couplings are briefly discussed. Possible experimental realization of the model in a modified quantum corral setup is suggested.

Uranium and manganese assembled in a wheel-shaped nanoscale single-molecule magnet with high spin-reversal barrier

Discrete molecular compounds that exhibit both magnetization hysteresis and slow magnetic relaxation below a characteristic 'blocking' temperature are known as single-molecule magnets. These are promising for applications including memory devices and quantum computing, but require higher spin-inversion barriers and hysteresis temperatures than currently achieved. After twenty years of research confined to the d-block transition metals, scientists are moving to the f-block to generate these properties. We have now prepared, by cation-promoted self-assembly, a large 5f-3d U(12)Mn(6) cluster that adopts a wheel topology and exhibits single-molecule magnet behaviour. This uranium-based molecular wheel shows an open magnetic hysteresis loop at low temperature, with a non-zero coercive field (below 4 K) and quantum tunnelling steps (below 2.5 K), which suggests that uranium might indeed provide a route to magnetic storage devices. This molecule also represents an interesting model for actinide nanoparticles occurring in the environment and in spent fuel separation cycles.

Application of Topological Optimization on Aluminum Alloy Automobile Wheel Designing

Topology optimization method based on variable density and the minimum compliance objective function was used on designing the wheel spokes. SIMP material interpolation model was established to compensate these deficiencies of variable density method. Considering manufacturing process and stress distribution, five bolt wheels was chose to topology optimization. The percentage of material removal of the optimal topology 40% was reasonable. Finite element analysis was used to test the strength and stiffness of the structure of the wheel, the result meets the requirements after wheel topology optimization, and reduces the quality of wheels to 7.76kg, achieve the goals of lightweight design.

Single‐Strand Molecular Wheels and Coordination Polymers in Copper(II) Benzoate Chemistry by the Employment of α‐Benzoin Oxime and Azides: Synthesis, Structures, and Magnetic Characterization

AbstractThe use of α‐benzoin oxime (bzoxH2) in copper(II) benzoate chemistry, in the absence or presence of ancillary azido ligands, is reported. The reaction of Cu(O2CPh)2·2H2O with one equivalent of bzoxH2 in N,N‐dimethylformamide (DMF) affords the decanuclear complex [Cu10(bzox)10(DMF)4] (1) in good yield. Dissolution of 1 in CH2Cl2 leads to the subsequent isolation of the solvent‐free complex [Cu10(bzox)10] (2) in moderate yields. Complexes 1 and 2 are isostructural and possess a loop or single‐strand molecular wheel topology. The bzox2– dianions behave as η1:η1:η2:μ3 ligands, which give rise to an overall [Cu10(μ‐ONR)10(μ‐OR′)10] core. Both 1 and 2 stack to form nanotubular columns with beautiful supramolecular architectures. The reaction of Cu(O2CPh)2·2H2O with bzoxH2 and NaN3 in a 1:1:1 molar ratio in MeOH gives the bzoxH2‐free complex [Cu(N3)(O2CPh)(MeOH)]n (3), which is a 1D chain. The CuII atoms in 3 are linked by a single, end‐on N3– group, a syn,syn‐η1:η1:μ PhCO2– ion, and an oxygen atom from the bridging MeOH ligand. The 1D chains are hydrogen bonded into 2D sheets through Nazide···H(OMeOH) interactions. Variable‐temperature, solid‐state direct‐current magnetic studies were carried out on 1–3. The data for 1 and 2 indicate very strong antiferromagnetic exchange interactions and a S = 0 ground state, which is expected for even‐membered loop arrays of CuII atoms. In contrast, 3 exhibits ferromagnetic exchange interactions; the data were fitted to the appropriate equation derived from the Hamiltonian H = –JΣ(Si·Si+1), which includes a zJ′ interchain interaction term. The best‐fit parameters were J = +49.6(4) cm–1, g = 2.067(3), and zJ′ = 2.3(1) K. The combined results demonstrate the ligating flexibility of both the bzoxH2 and azido groups and their usefulness in the synthesis of polynuclear CuII clusters and coordination polymers.

Analysis of Numerical Grinding Wheel Topology and Experimental Measurement

Analysis of Numerical Grinding Wheel Topology and Experimental Measurement

Inside Cover: A [Mn32] Double-Decker Wheel (Angew. Chem. Int. Ed. 19/2011)

A mixed-valent [Mn32] cluster with a very unusual “double-decker” wheel topology is described by E. K. Brechin, A. J. Tasiopoulos et al. in their Communication on page 4441 ff. It is by far the highest-nuclearity example of its type and one of the largest known manganese clusters, and it displays single-molecule-magnet behavior with the largest effective barrier to magnetization relaxation of any molecular wheel.

Initial employment of α-benzoin oxime as a route to high-nuclearity metal clusters: decanuclear CuII complexes with a wheel topology

The initial employment of alpha-benzoin oxime (bzoxH2) in metal cluster chemistry has provided access to a new family of decanuclear CuII complexes with a loop or single-strand wheel topology; the CuII10 clusters are antiferromagnetically-coupled with an S=0 spin ground state, as expected for even-membered loop arrays of CuII atoms.