A computational fluid dynamic investigation of inhomogeneous hydrogen flame acceleration and transition to detonation

Gas explosions in homogeneous reactive mixtures have been widely studied both experimentally and numerically. However, in practice and industrial applications, combustible mixtures are usually inhomogeneous and subject to vertical concentration gradients. Limited studies have been conducted in such context which resulted in limited understanding of the explosion characteristics in such situations. The present numerical investigation aims to study the dynamics of Deflagration to Detonation Transition (DDT) in inhomogeneous hydrogen/air mixtures and examine the effects of obstacle blockage ratio in DDT. VCEFoam, a reactive density-based solver recently assembled by the authors within the frame of OpenFOAM CFD toolbox has been used. VCEFoam uses the Harten–Lax–van Leer–Contact (HLLC) scheme fr the convective fluxes contribution and shock capturing. The solver has been verified by comparing its predictions with the analytical solutions of two classical test cases. For validation, the experimental data of Boeck et al. (1) is used. The experiments were conducted in a rectangular channel the three different blockage ratios and hydrogen concentrations. Comparison is presented between the predicted and measured flame tip velocities. The shaded contours of the predicted temperature and numerical Schlieren (magnitude of density gradient) will be analysed to examine the effects of the blockage ratio on flame acceleration and DDT

The distorting effect of deciding to stop sampling

usually collect information to serve specific goals andoften end up with samples that are unrepresentative of the un-derlying population. This can introduce biases on later judg-ments that generalize from these samples. Here we show thatgoals influence not only what information we collect, but alsowhen we decide to terminate search. Using an optimal stop-ping analysis, we demonstrate that even when learners have nocontrol over the content of a sample (i.e., natural sampling),the simple decision of when to stop sampling can yield sampledistributions that are non-representative and could potentiallybias future decision making. We test the prediction of thesetheoretical analyses with two behavioral experiment

Ask or Tell: Balancing questions and instructions in intuitive teaching

Teaching is an intuitive social activity that requires reason-ing about and influencing the mind of others. A good teacherforms a belief about the knowledge of their student, asks clar-ifying questions, and gives instructions or explanations to tryto induce a target concept in the student’s mind. We proposePartially Observable Markov Decision Processes (POMDPs)as a model of intuitive human teaching. According to this ac-count, teachers make pedagogical decisions with uncertaintyabout the knowledge state of their student. In two behavioralexperiments, human participants were tasked with balancingassessments (asking questions) and instructions to help teach astudent to build a tower of colored blocks. Human behavior inthe task was compared to the performance of a computerizedteaching algorithm optimized to solve the equivalent POMDP.Our results show that humans favor asking questions and estab-lishing common ground during teaching even at an economiccost and increase question asking as uncertainty grows

Predictable stimulus onsets improve memory

Exploring and remembering are fundamental to many human activities. Characterizing influences on recognitionmemory can help clarify the workings of memory systems and facilitate design of effective learning environments. Studies ofself-directed learning show that a key determinant of self-directed benefits is in choosing when to see the next stimulus, butthese results do not establish whether it is the act of choosing or the knowledge of stimulus arrival times that primarily matters.We disentangle these factors by asking whether predictable stimulus timing that is not under participant control still leads to amemory benefit. Participants saw pictures of objects one at a time with either a constant or unpredictable inter-stimulus interval(ISI) and showed better memory with constant timing across a range of ISIs. These results speak to interactions betweenattention and memory, the efficiency of study protocols, and the factors influencing effective self-directed learning

Stochastic accumulation of feature information in perception and memory

It is now well established that the time course of perceptual processing influences the first second or so of performance in a wide variety of cognitive tasks. Over the last20 years, there has been a shift from modeling the speed at which a display is processed, to modeling the speed at which different features of the display are perceived and formalizing how this perceptual information is used in decision making. The first of these models(Lamberts, 1995) was implemented to fit the time course of performance in a speeded perceptual categorization task and assumed a simple stochastic accumulation of feature information. Subsequently, similar approaches have been used to model performance in a range of cognitive tasks including identification, absolute identification, perceptual matching, recognition, visual search, and word processing, again assuming a simple stochastic accumulation of feature information from both the stimulus and representations held in memory. These models are typically fit to data from signal-to-respond experiments whereby the effects of stimulus exposure duration on performance are examined, but response times (RTs) and RT distributions have also been modeled. In this article, we review this approach and explore the insights it has provided about the interplay between perceptual processing, memory retrieval, and decision making in a variety of tasks. In so doing, we highlight how such approaches can continue to usefully contribute to our understanding of cognition

Desirable difficulties in the development of active inquiry skills

This study explores developmental changes in the ability toask informative questions. We hypothesized an intrinsic linkbetween the ability to update beliefs in light of evidence andthe ability to ask informative questions. Four- to ten-year-oldchildren played an iPad game asking them to identify a hiddenbug. Learners could either ask about individual bugs, or makea series of feature queries (e.g., “Does the hidden bug haveantenna?”) that could more efficiently narrow the hypothesisspace. Critically the task display either helped children inte-grate evidence with the hypothesis space or required them toperform this operation themselves. Although we found thathelping children update their beliefs improved some aspects oftheir active inquiry behavior, children required to update theirown beliefs asked questions that were more context-sensitiveand thus informative. The results show how making a taskmore difficult may actually improve children’s active inquiryskills, thus illustrating a type of desirable difficulty

The Attentional Learning Trap and How to Avoid It

People often make repeated decisions from experience. In such scenarios, persistent biases of choice can develop, most notably the “hot stove effect” (Denrell & March, 2001) in which a prospect that is mistakenly believed to be negative is avoided and thus belief-correcting information is never obtained. In the existing literature, the hot stove effect is generally thought of as developing through interaction with a single, stochastic prospect. Here, we show how a similar bias can develop due to people’s tendency to selectively attend to a subset of features during categorization. We first explore the bias through model simulation, then report on an experiment in which we find evidence of a decisional bias linked to selective attention. Finally, we use these computational models to design novel interventions to “de-bias” decision-makers, some of which may have practical applicatio

The critical moment is coming:Modeling the dynamics of suspense

Suspense is an affective state that contributes to our enjoy-ment of experiences such as movies and sports. Ely, Frankel,and Kamenica (2015) proposed a formal definition of suspensewhich depends on the variance of subjective future beliefsabout an outcome of interest (e.g., winning a game). In orderto evaluate this theory, we designed a task based on the cardgame Blackjack where a variety of suspense dynamics can beexperimentally induced. By presenting participants with iden-tical sequences of information (i.e., card draws), but manip-ulating contextual knowledge (i.e., their understanding of therules of the game) we were able to show that self-reported sus-pense follows the predictions of the model. Follow-up modelcomparison further showed an advantage for the “suspense asvariance of future beliefs” account over a number of alterna-tive definitions of suspense, including some that depend onlyon current uncertainty (not the future). This paper is an initialattempt to link aspects of formal models of information anduncertainty with affective cognitive states

Workshop Proposal: Contemporary Cognitive Approaches to Decision-Making

The study of how people make judgments and decision