Droplet size development in a DISI injector fuel spray

In this work, Phase Doppler Anemometry (PDA) measurements are used to test the hypothesis that the mean droplet size in Direct Injection Spark Ignition (DISI) engine fuel spray increases with distance from the injector due to the evaporation of the smaller droplets. In order to understand the role of evaporation, two velocity components and drop size PDA measurements were performed for one plume of a DISI injector using two fuels with widely differing vapour pressures. The measurements were taken along the plume centreline at four different vertical distances from the injector tip between 20 to 50 mm. on the plume centreline to evaluate the development of droplet size distributions along the plume. Measurements are also made across the plume (perpendicular to the plume centreline) at the 30 and 50 mm locations. Measurements using PDA closer to the injector are more difficult due to the high spray density (particularly apparent at 20mm or closer to the injector). A data fitting process is suggested using joint probability distribution functions (JPDFs) to reduce the effect of statistical significance where data rates are low. This improves the description of the PDA derived drop size distribution in regions where the data validation rate is poor. It is found that the evaporation is not the main cause for droplet size increase along the plume. The most likely reason for the increase of the Sauter Mean Diameter (SMD) with distance from the injector is that the smaller droplets move away from the plume centreline through turbulent diffusion at a higher rate compared to larger droplets. Higher axial momentum of the larger droplets reduces their response to turbulent velocity fluctuations and hence their path-lines are less prone to stray from their initial trajectory

Impact of gasoline direct injection fuel injector hole geometry on spray characteristics under flash boiling and ambient conditions

The effect of injector nozzle design on the Gasoline Direct Injection (GDI) fuel spray characteristics under atmospheric and flash boiling conditions was investigated using Phase Doppler Anemometry (PDA) measurements. To understand the impact of hole diameter and conicity, experiments were conducted on two bespoke 3-hole injectors in a pressure and temperature controlled constant volume chamber and in the open air. The measurements were taken radially outward from the injector axis to the outer extent of the plume at distances of 15 mm, 25 mm and 40 mm from the injector tip. Observations of the influence of surrounding gas and temperature conditions and hole design on the injector spray performance were made. Under non-flash boiling conditions, it was found that the injection pressure dictates the length of the spray penetration before collapse occurs, with an increase in pressure resulting in an increase in this length. Comparison of mean velocity and droplet diameter data are also made to understand the performance under flash boiling conditions. Results show that, under flash boiling conditions, the droplet velocity significantly increases while the droplet size reduces. More importantly, it is found that the impact of the flash boiling environment on sprays of different hole geometries is different. Some hole designs offer more resistance against spray collapse. It was found that the mid-sized of the three hole diameters tested here was found to produce a spray that more readily collapsed than that of the smaller or larger hole diameters. In addition, it was found that under flash boiling conditions, the convergent hole had a greater propensity to exhibit spray collapse

Experimental investigation of the effect of high pressure nozzle geometry on spray characteristics

Phase Doppler Anemometry (PDA) measurements [1] are applied to low length to diameter ratio (L/D) multi-hole nozzles operating with at high fuel pressure (20 MPa) that are implemented in the new Euro6 generation of Gasoline Direct Injection engines. For these multi-jets spray, the authors intend to demonstrate; the importance of the spray shape, the effect of hole design and the reorganisation dynamic of the drop size distribution by turbulent mixing. To do so, we report significant experimental effort along with careful data reduction, exercised to understand the spray behaviour, in particular separating the sources of experimental uncertainty from the flow physics. A practical methodology is adopted as a compromise between measurement effort, error removal, and the need to understand underlying physical processes within the spray plume. The present work focuses mostly on the drop size and velocity profiles (two-component) perpendicular to the plume direction

The Compositional Nature of Event Representations in the Human Brain

How does the human brain represent simple compositions of constituents: actors, verbs, objects, directions, and locations? Subjects viewed videos during neuroimaging (fMRI) sessions from which sentential descriptions of those videos were identified by decoding the brain representations based only on their fMRI activation patterns. Constituents (e.g., fold and shirt) were independently decoded from a single presentation. Independent constituent classification was then compared to joint classification of aggregate concepts (e.g., fold-shirt); results were similar as measured by accuracy and correlation. The brain regions used for independent constituent classification are largely disjoint and largely cover those used for joint classification. This allows recovery of sentential descriptions of stimulus videos by composing the results of the independent constituent classifiers. Furthermore, classifiers trained on the words one set of subjects think of when watching a video can recognise sentences a different subject thinks of when watching a different video

Managing toxicities associated with immune checkpoint inhibitors: consensus recommendations from the Society for Immunotherapy of Cancer (SITC) Toxicity Management Working Group.

Cancer immunotherapy has transformed the treatment of cancer. However, increasing use of immune-based therapies, including the widely used class of agents known as immune checkpoint inhibitors, has exposed a discrete group of immune-related adverse events (irAEs). Many of these are driven by the same immunologic mechanisms responsible for the drugs\u27 therapeutic effects, namely blockade of inhibitory mechanisms that suppress the immune system and protect body tissues from an unconstrained acute or chronic immune response. Skin, gut, endocrine, lung and musculoskeletal irAEs are relatively common, whereas cardiovascular, hematologic, renal, neurologic and ophthalmologic irAEs occur much less frequently. The majority of irAEs are mild to moderate in severity; however, serious and occasionally life-threatening irAEs are reported in the literature, and treatment-related deaths occur in up to 2% of patients, varying by ICI. Immunotherapy-related irAEs typically have a delayed onset and prolonged duration compared to adverse events from chemotherapy, and effective management depends on early recognition and prompt intervention with immune suppression and/or immunomodulatory strategies. There is an urgent need for multidisciplinary guidance reflecting broad-based perspectives on how to recognize, report and manage organ-specific toxicities until evidence-based data are available to inform clinical decision-making. The Society for Immunotherapy of Cancer (SITC) established a multidisciplinary Toxicity Management Working Group, which met for a full-day workshop to develop recommendations to standardize management of irAEs. Here we present their consensus recommendations on managing toxicities associated with immune checkpoint inhibitor therapy

Seeing is Worse than Believing: Reading People’s Minds Better than Computer-Vision Methods Recognize Actions

We had human subjects perform a one-out-of-six class action recognition task from video stimuli while undergoing functional magnetic resonance imaging (fMRI). Support-vector machines (SVMs) were trained on the recovered brain scans to classify actions observed during imaging, yielding average classification accuracy of 69.73% when tested on scans from the same subject and of 34.80% when tested on scans from different subjects. An apples-to-apples comparison was performed with all publicly available software that implements state-of-the-art action recognition on the same video corpus with the same cross-validation regimen and same partitioning into training and test sets, yielding classification accuracies between 31.25% and 52.34%. This indicates that one can read people’s minds better than state-of-the-art computer-vision methods can perform action recognition.This work was supported, in part, by the Center for Brains, Minds and Machines (CBMM), funded by NSF STC award CCF - 1231216. AB, DPB, NS, and JMS were supported, in part, by Army Research Laboratory (ARL) Cooperative Agreement W911NF-10-2-0060, AB, in part, by the Center forBrains, Minds and Machines (CBMM), funded by NSF STC award CCF-1231216, WC, CX, and JJC, in part, by ARL Cooperative Agreement W911NF-10-2-0062 and NSF CAREER grant IIS-0845282, CDF, in part, by NSF grant CNS-0855157, CH and SJH, in part, by the McDonnell Foundation, and BAP, in part, by Science Foundation Ireland grant 09/IN.1/I2637

Time- but not sleep-dependent consolidation promotes the emergence of cross-modal conceptual representations

Conceptual knowledge about objects comprises a diverse set of multi-modal and generalisable information, which allows us to bring meaning to the stimuli in our environment. The formation of conceptual representations requires two key computational challenges: integrating information from different sensory modalities and abstracting statistical regularities across exemplars. Although these processes are thought to be facilitated by offline memory consolidation, investigations into how cross-modal concepts evolve offline, over time, rather than with continuous category exposure are still missing. Here, we aimed to mimic the formation of new conceptual representations by reducing this process to its two key computational challenges and exploring its evolution over an offline retention period. Participants learned to distinguish between members of two abstract categories based on a simple one-dimensional visual rule. Underlying the task was a more complex hidden indicator of category structure, which required the integration of information across two sensory modalities. In two experiments we investigated the impact of time- and sleep-dependent consolidation on category learning. Our results show that offline memory consolidation facilitated cross-modal category learning. Surprisingly, consolidation across wake, but not across sleep showed this beneficial effect. By demonstrating the importance of offline consolidation the current study provided further insights into the processes that underlie the formation of conceptual representations