Analysis and optimization of gel-cast ceramic foam diesel particulate filter performance

Gel-cast ceramic foams potentially offer a more robust configurable alternative filtration medium to monolithic wall flow filters (WFFs) for the reduction in particulate matter (PM) emissions from diesel internal combustion engines. The fundamental back pressure and filtration efficiency characteristics of gel-cast ceramic foam diesel particulate filters (DPFs) have been investigated. Methodology is developed for the first time that allows the calculation of the effect of local PM loading on the pressure drop characteristics from experimental data without problems caused by the non-uniform PM loading in the filter that can be applied to all depth bed filtration media. The back pressure and filtration efficiency relationships were used to develop graphical design spaces to aid development of application-specific DPFs. Effects of PM distribution on the pressure drop of the filter are presented. Filters with a non-even distribution of PM were found to have lower pressure drops than filters with an evenly distributed PM for the same average specific PM loadings. The predictions showed that gel-cast ceramic foams can achieve comparable back pressure, filtration volume, and PM holding capacity with WFFs with a lower filtration efficiency of about 80 per cent. The model demonstrated that greater than 90 per cent filtration efficiency can be achieved with filter volumes of about 0.6 times the volume of a WFF with a lower PM holding capacity

Measuring pore diameter distribution of gelcast ceramic foams from two-dimensional cross sections

Increasing applications for gelcast ceramic foams is making the effective, accurate and cost effective measurement of pore diameter and distribution of significant value to a wide range of research fields. Current methods either do not directly measure pore diameter or they require high equipment and time costs. Measuring pore diameter directly from sample cross sections is both rapid and cost effective but, due to the random nature of the pore location during sectioning of the sample, it under predicts the pore diameter. The proposed method identified that the mean measured pore diameter was 79% (2 s.f.) of the actual pore diameter. Numerical methods for correcting the pore distribution as well as the average pore diameter are presented

Modelling gas flow pressure gradients in Gelcast ceramic foam diesel particulate filters

New mathematical models are proposed that predict fluid flow pressure gradients in gelcast ceramic foam diesel exhaust particulate filters by considering the foam structure conceptually as serially connected orifices. The resulting multiple orifice mathematical (MOM) model is based on the sum of a viscous term derived from an extended Ergun model and the kinetic energy loss derived from the Bernoulli and conservation of mass equations. The MOM model was calibrated using experimental data obtained from measuring the air flowrate and pressure drop across a physical large-scale three-dimensional model of a cellular foam structure produced using rapid manufacturing techniques. The calibrated model was then validated using fluid flow data obtained from gelcast ceramic foam filters of various cell sizes and was found to require no empirical recalibration for each gelcast ceramic foam sample. The MOM model for clean filters was extended to predict pressure gradients of filters loaded with particulate matter (PM). The prediction of pressure gradients through gelcast ceramic filters using the MOM model for clean and PM-loaded cases was shown to be in reasonable agreement with experimental data. The models were finally applied to design a filter for a turbocharged, charge-cooled, 2.0 l, fourstroke, common rail, direct injection passenger car diesel engine

Low power auto selective regeneration of monolithic wall flow diesel particulate filters

This paper presents research into a novel autoselective electric discharge method for regenerating monolithic wall flow diesel particulate filters using low power over the entire range of temperatures and oxygen concentrations experienced within the exhaust systems of modern diesel engines. The ability to regenerate the filter independently of exhaust gas temperature and composition significantly reduces system complexity compared to other systems. In addition, the system does not require catalyst loading and uses only massproduced electronic and electrical components, thus reducing the cost of the after-treatment package. Purpose built exhaust gas simulation test rigs were used to evaluate, develop and optimise the autoselective regeneration system. On-engine testing demonstrated the performance of the autoselective regeneration process under real engine conditions. Typical regeneration performance is presented and discussed with the aid of visual observations, particulate mass measurements, back pressure measurements and energy consumption. The research demonstrates the potential of the novel autoselective method for diesel particulate filter regeneration. The autoselective process does not require an exhaust by-pass and enables the system to be low power, catalyst-free and exhaust temperature independent

The performance of the jet trigger for the ATLAS detector during 2011 data taking

The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton–proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon–nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction

Constraints on spin-0 dark matter mediators and invisible Higgs decays using ATLAS 13 TeV pp collision data with two top quarks and missing transverse momentum in the final state

This paper presents a statistical combination of searches targeting final states with two top quarks and invisible particles, characterised by the presence of zero, one or two leptons, at least one jet originating from a b-quark and missing transverse momentum. The analyses are searches for phenomena beyond the Standard Model consistent with the direct production of dark matter in pp collisions at the LHC, using 139 fb−1 of data collected with the ATLAS detector at a centre-of-mass energy of 13 TeV. The results are interpreted in terms of simplified dark matter models with a spin-0 scalar or pseudoscalar mediator particle. In addition, the results are interpreted in terms of upper limits on the Higgs boson invisible branching ratio, where the Higgs boson is produced according to the Standard Model in association with a pair of top quarks. For scalar (pseudoscalar) dark matter models, with all couplings set to unity, the statistical combination extends the mass range excluded by the best of the individual channels by 50 (25) GeV, excluding mediator masses up to 370 GeV. In addition, the statistical combination improves the expected coupling exclusion reach by 14% (24%), assuming a scalar (pseudoscalar) mediator mass of 10 GeV. An upper limit on the Higgs boson invisible branching ratio of 0.38 (0.30+0.13−0.09) is observed (expected) at 95% confidence level

Study of Z → llγ decays at √s = 8 TeV with the ATLAS detector

This paper presents a study of Z → llγ decays with the ATLAS detector at the Large Hadron Collider. The analysis uses a proton–proton data sample corresponding to an integrated luminosity of 20.2 fb−1 collected at a centre-ofmass energy √s = 8 TeV. Integrated fiducial cross-sections together with normalised differential fiducial cross-sections, sensitive to the kinematics of final-state QED radiation, are obtained. The results are found to be in agreement with stateof-the-art predictions for final-state QED radiation. First measurements of Z → llγ γ decays are also reported

Search for heavy Majorana or Dirac neutrinos and right-handed W gauge bosons in final states with charged leptons and jets in pp collisions at √s = 13 TeV with the ATLAS detector

A search for heavy right-handed Majorana or Dirac neutrinos NR and heavy right-handed gauge bosons WR is performed in events with energetic electrons or muons, with the same or opposite electric charge, and energetic jets. The search is carried out separately for topologies of clearly separated final-state products (“resolved” channel) and topologies with boosted final states with hadronic and/or leptonic products partially overlapping and reconstructed as a large-radius jet (“boosted” channel). The events are selected from pp collision data at the LHC with an integrated luminosity of 139 fb−1 collected by the ATLAS detector at √s = 13 TeV. No significant deviations from the Standard Model predictions are observed. The results are interpreted within the theoretical framework of a left-right symmetric model, and lower limits are set on masses in the heavy righthanded WR boson and NR plane. The excluded region extends to about m(WR) = 6.4 TeV for both Majorana and Dirac NR neutrinos at m(NR) < 1 TeV. NR with masses of less than 3.5 (3.6) TeV are excluded in the electron (muon) channel at m(WR) = 4.8 TeV for the Majorana neutrinos, and limits of m(NR) up to 3.6 TeV for m(WR) = 5.2 (5.0) TeV in the electron (muon) channel are set for the Dirac neutrinos. These constitute the most stringent exclusion limits to date for the model considered

Deep generative models for fast photon shower simulation in ATLAS

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques