Experimental investigation into the effect of magnetic fuel reforming on diesel combustion and emissions running on wheat germ and pine oil

© 2019 Elsevier B.V. All rights reserved.The present study aims to explore the effect of fuel ionisation on engine performance, emission and combustion characteristics of a twin cylinder compression ignition (CI) engine running on biofuel. Wheat germ oil (WGO) and pine oil (PO) have been identified as diesel fuel surrogates with high and low viscosities, respectively. High viscosity biofuels result in incomplete combustion due to poor atomisation and evaporation which ultimately leads to insufficient air-fuel mixing to form a combustible mixture. Consequently, engines running on this type of fuel suffer from lower brake thermal efficiency (BTE) and higher soot emission. In contrast, low viscosity biofuels exhibit superior combustion characteristics however they have a low cetane number which causes longer ignition delay and therefore higher NO emission. To overcome the limitations of both fuels, a fuel ionisation filter (FIF) with a permanent magnet is installed upstream of the fuel pump which electrochemically ionises the fuel molecules and aids in quick dispersion of the ions. The engine used in this investigation is a twin cylinder tractor engine that runs at a constant speed of 1500 rpm. The engine was initially run on diesel to warm-up before switching to WGO and PO, this was mainly due to poor cold start performance characteristics of both fuels. At 100% load, BTE for WGO is reduced by 4% compared to diesel and improved by 7% with FIF. In contrast, BTE for PO is 4% higher compared to diesel, however, FIF has minimal effect on BTE when running on PO. Although, smoke, HC and CO emissions were higher for WGO compared to diesel, they were lower with FIF due to improved combustion. These emissions were consistently lower for PO due to superior combustion performance, mainly attributed to low viscosity of the fuel. However, NO emission for PO (1610 ppm) is higher compared to diesel (1580 ppm) at 100% load and reduced with FIF (1415 ppm). NO emission is reduced by approximately 12% for PO+FIF compared to PO. The results suggest that FIF has the potential to improve diesel combustion performance and reduce NO emission produced by CI engines running on high and low viscosity biofuels, respectively.Peer reviewe

Over-limiting Current and Control of Dendritic Growth by Surface Conduction in Nanopores

Understanding over-limiting current (faster than diffusion) is a long-standing challenge in electrochemistry with applications in desalination and energy storage. Known mechanisms involve either chemical or hydrodynamic instabilities in unconfined electrolytes. Here, it is shown that over-limiting current can be sustained by surface conduction in nano pores, without any such instabilities, and used to control dendritic growth during electrodeposition. Copper electrode posits are grown in anodized aluminum oxide membranes with polyelectrolyte coatings to modify the surface charge. At low currents, uniform electroplating occurs, unaffected by surface modification due to thin electric double layers, but the morphology changes dramatically above the limiting current. With negative surface charge, growth is enhanced along the nanopore surfaces, forming surface dendrites and nanotubes behind a deionization shock. With positive surface charge, dendrites avoid the surfaces and are either guided along the nanopore centers or blocked from penetrating the membrane

A quantum Jensen-Shannon graph kernel using discrete-time quantum walks

In this paper, we develop a new graph kernel by using the quantum Jensen-Shannon divergence and the discrete-time quantum walk. To this end, we commence by performing a discrete-time quantum walk to compute a density matrix over each graph being compared. For a pair of graphs, we compare the mixed quantum states represented by their density matrices using the quantum Jensen-Shannon divergence. With the density matrices for a pair of graphs to hand, the quantum graph kernel between the pair of graphs is defined by exponentiating the negative quantum Jensen-Shannon divergence between the graph density matrices. We evaluate the performance of our kernel on several standard graph datasets, and demonstrate the effectiveness of the new kernel

An edge-based matching kernel through discrete-time quantum walks

In this paper, we propose a new edge-based matching kernel for graphs by using discrete-time quantum walks. To this end, we commence by transforming a graph into a directed line graph. The reasons of using the line graph structure are twofold. First, for a graph, its directed line graph is a dual representation and each vertex of the line graph represents a corresponding edge in the original graph. Second, we show that the discrete-time quantum walk can be seen as a walk on the line graph and the state space of the walk is the vertex set of the line graph, i.e., the state space of the walk is the edges of the original graph. As a result, the directed line graph provides an elegant way of developing new edge-based matching kernel based on discrete-time quantum walks. For a pair of graphs, we compute the h-layer depth-based representation for each vertex of their directed line graphs by computing entropic signatures (computed from discrete-time quantum walks on the line graphs) on the family of K-layer expansion subgraphs rooted at the vertex, i.e., we compute the depth-based representations for edges of the original graphs through their directed line graphs. Based on the new representations, we define an edge-based matching method for the pair of graphs by aligning the h-layer depth-based representations computed through the directed line graphs. The new edge-based matching kernel is thus computed by counting the number of matched vertices identified by the matching method on the directed line graphs. Experiments on standard graph datasets demonstrate the effectiveness of our new kernel

Role of Copper Oxide Layer on Pool Boiling Performance with Femtosecond Laser Processed Surfaces

Copper pool boiling surfaces are tested for pool boiling enhancement due to femtosecond laser surface processing (FLSP). FLSP creates self-organized micro/nanostructures on metallic surfaces and creates highly wetting and wicking surfaces with permanent surface features. In this study two series of samples were created. The first series consists of three flat FLSP copper surfaces with varying microstructures and the second series is an open microchannel configuration with laser processing over the horizontal surfaces of the microchannels. These microchannels range in height from 125 microns to 380 microns. Each of these surfaces were tested for pool boiling performance. It was found that all the processed surfaces except one resulted in a decrease in critical heat flux and heat transfer coefficient compared to an unprocessed surface. It was found that the laser fluence parameter had a significant role in whether there was an increase in CHF or HTC. A cross sectioning technique was employed to study the different layers of the microstructure and to understand how FLSP could have a negative effect on the CHF and HTC. It was found that a thick oxide layer forms during the FLSP process of copper in an open-air atmosphere. The thickness and uniformity of the oxide layer is highly dependent on the laser fluence. A low fluence sample results in an inconsistent oxide layer of nonuniform thickness and subsequently an increase in CHF and HTC. A high laser fluence sample results in a uniformly thick oxide layer which increases the thermal resistance of the sample and allows for a premature CHF and decrease in HTC

A new column-generation-based algorithm for VMAT treatment plan optimization

We study the treatment plan optimization problem for volumetric modulated arc therapy (VMAT). We propose a new column-generation-based algorithm that takes into account bounds on the gantry speed and dose rate, as well as an upper bound on the rate of change of the gantry speed, in addition to MLC constraints. The algorithm iteratively adds one aperture at each control point along the treatment arc. In each iteration, a restricted problem optimizing intensities at previously selected apertures is solved, and its solution is used to formulate a pricing problem, which selects an aperture at another control point that is compatible with previously selected apertures and leads to the largest rate of improvement in the objective function value of the restricted problem. Once a complete set of apertures is obtained, their intensities are optimized and the gantry speeds and dose rates are adjusted to minimize treatment time while satisfying all machine restrictions. Comparisons of treatment plans obtained by our algorithm to idealized IMRT plans of 177 beams on five clinical prostate cancer cases demonstrate high quality with respect to clinical dose–volume criteria. For all cases, our algorithm yields treatment plans that can be delivered in around 2 min. Implementation on a graphic processing unit enables us to finish the optimization of a VMAT plan in 25–55 s.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98593/1/0031-9155_57_14_4569.pd

Integral dose investigation of non‐coplanar treatment beam geometries in radiotherapy

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134886/1/mp5055.pd