Combustion control of DME HCCI using charge dilution and spark assistance.

To realize the potential of DME for clean combustion, fueling control is essential. In this research, the challenges, advantages, and applicability of high-pressure direct injection and low-pressure port injection are reviewed and evaluated, especially in relevance to HCCI combustion. In this study, emphasis is given to the applicable ranges of low-pressure fuel delivery in relevance to load, air-fuel ratio, and inert gas dilution, for realizing HCCI combustion. The strategy of high-pressure direct injection is advantageous for combustion phasing control, but the fuel handling is challenging because of the high vapor pressure of DME fuel. The strategy of port fuel injection is prone to early combustion and, consequently, tends to produce excessive pressure rise rates in the combustion chamber. This challenge is escalated at higher engine loads, making homogenous charge compression ignition difficult to achieve. In this paper, the load extension of DME-fueled HCCI combustion was explored. First, the impact of dilution on the combustion characteristics of DME HCCI was studied under lean and CO2 diluted conditions. Under the present empirical setups, results show that the lean-burn strategy has limited capability of combustion phasing control, especially when the engine load is above 5 bar IMEP. The CO2 dilution strategy can significantly retard the combustion phasing until the fulfillment of combustion becomes unstable. It was found that spark assistance is advantageous for combustion control. With an effective application of excess air, intake CO2 dilution and spark assistance, an engine load of 8 bar IMEP was reached with appropriate combustion phasing, with ultra-low NOx emissions.

Subcritical escape waves in schooling fish.

Theoretical physics predicts optimal information processing in living systems near transitions (or pseudo-critical points) in their collective dynamics. However, focusing on potential benefits of proximity to a critical point, such as maximal sensitivity to perturbations and fast dissemination of information, commonly disregards possible costs of criticality in the noisy, dynamic environmental contexts of biological systems. Here, we find that startle cascades in fish schools are subcritical (not maximally responsive to environmental cues) and that distance to criticality decreases when perceived risk increases. Considering individuals' costs related to two detection error types, associated to both true and false alarms, we argue that being subcritical, and modulating distance to criticality, can be understood as managing a trade-off between sensitivity and robustness according to the riskiness and noisiness of the environment. Our work emphasizes the need for an individual-based and context-dependent perspective on criticality and collective information processing and motivates future questions about the evolutionary forces that brought about a particular trade-off.

Collective detection based on visual information in animal groups.

We investigate key principles underlying individual, and collective, visual detection of stimuli, and how this relates to the internal structure of groups. While the individual and collective detection principles are generally applicable, we employ a model experimental system of schooling golden shiner fish (Notemigonus crysoleucas) to relate theory directly to empirical data, using computational reconstruction of the visual fields of all individuals. This reveals how the external visual information available to each group member depends on the number of individuals in the group, the position within the group, and the location of the external visually detectable stimulus. We find that in small groups, individuals have detection capability in nearly all directions, while in large groups, occlusion by neighbours causes detection capability to vary with position within the group. To understand the principles that drive detection in groups, we formulate a simple, and generally applicable, model that captures how visual detection properties emerge due to geometric scaling of the space occupied by the group and occlusion caused by neighbours. We employ these insights to discuss principles that extend beyond our specific system, such as how collective detection depends on individual body shape, and the size and structure of the group.

Stability and responsiveness in a self-organized living architecture.

Robustness and adaptability are central to the functioning of biological systems, from gene networks to animal societies. Yet the mechanisms by which living organisms achieve both stability to perturbations and sensitivity to input are poorly understood. Here, we present an integrated study of a living architecture in which army ants interconnect their bodies to span gaps. We demonstrate that these self-assembled bridges are a highly effective means of maintaining traffic flow over unpredictable terrain. The individual-level rules responsible depend only on locally-estimated traffic intensity and the number of neighbours to which ants are attached within the structure. We employ a parameterized computational model to reveal that bridges are tuned to be maximally stable in the face of regular, periodic fluctuations in traffic. However analysis of the model also suggests that interactions among ants give rise to feedback processes that result in bridges being highly responsive to sudden interruptions in traffic. Subsequent field experiments confirm this prediction and thus the dual nature of stability and flexibility in living bridges. Our study demonstrates the importance of robust and adaptive modular architecture to efficient traffic organisation and reveals general principles regarding the regulation of form in biological self-assemblies.

The dynamics of coordinated group hunting and collective information transfer among schooling prey.

Predator-prey interactions are vital to the stability of many ecosystems. Yet, few studies have considered how they are mediated due to substantial challenges in quantifying behavior over appropriate temporal and spatial scales. Here, we employ high-resolution sonar imaging to track the motion and interactions among predatory fish and their schooling prey in a natural environment. In particular, we address the relationship between predator attack behavior and the capacity for prey to respond both directly and through collective propagation of changes in velocity by group members. To do so, we investigated a large number of attacks and estimated per capita risk during attack and its relation to the size, shape, and internal structure of prey groups. Predators were found to frequently form coordinated hunting groups, with up to five individuals attacking in line formation. Attacks were associated with increased fragmentation and irregularities in the spatial structure of prey groups, features that inhibit collective information transfer among prey. Prey group fragmentation, likely facilitated by predator line formation, increased (estimated) per capita risk of prey, provided prey schools were maintained below a threshold size of approximately 2 m(2). Our results highlight the importance of collective behavior to the strategies employed by both predators and prey under conditions of considerable informational constraints.