Effect of Out-Gassing on the Onset of Hypersonic Boundary Layer Transition

Prediction and control of the onset of transition and the associated variation in aerothermodynamic parameters in high-speed flows is key to optimize the performance and design of Thermal Protection Systems (TPS) of next-generation aerospace vehicles [1]. Boundary Layer Transition (BLT) characteristics can influence the surface heating budget determining the TPS thickness and consequently its weight penalty. Ablative heatshields are designed to alleviate the high heat flux at the surface through pyrolysis of their polymeric matrix and subsequent fiber ablation [2]. Pyrolysis leads to out-gassing and non-uniform ablation lead to surface roughness, both of which are known to influence the transition process. An ablator impacts BLT through three main routes: gas injecting into the boundary layer from the wall, changing the surface heat transfer due to wall-flow chemical reactions, and modifying surface roughness [3]. In preparation to Mars 2020 mission post-flight analysis, the predictive transition capability has been initiated toward hard-coupling porous material response analysis and aerothermal environment calculation

The sum of the parts is greater than the whole: Multi-scalar socio-spatial definitions of identity in Karachi's Muhajir majority areas

Notions of identity and community like space consist of varying scales of definition and interaction ranging from concepts of nationhood and nationality through to local solidarities and affiliations of religion, trade, caste etc. Space Syntax research suggests that most people belong to communities that are both spatial and transpatial in nature where inhabitants of an area are bound not only to the people and spaces they physically inhabit but are simultaneously part of a larger transpatial community independent of the immediate physical context. In the context of Karachi's Muhajir community, an ethno-political entity that has evolved through spatio-political constraints applied to an amalgam of assorted post-Partition urban minority groups, these socio-spatial variations in definition of identity can be studied across the changing scale of the city. Using space syntax methodologies, this paper examines the spatial definitions of identity, i.e. how affiliations and solidarities vary across the changing scales of the city and, how the use and positioning of communal tools of identification organize and articulate spatial clusters. This study used a range of sources to map religious and political institutions as well as on-site documentation of political propaganda and related the location of these features to space syntax models of the city and four case study settlements. The intention was to analyse the accessibility and clustering of various communal spaces, how spatial configuration defines the social role communal spaces play within the community and how they may define the spatial limits of sub-clusters and internal social hierarchies of the community. This multi-scalar analysis will show that not only does the nature of the muhajir cluster change across the various scales of the city, the nature and scale of the interface between the community and the city changes too. At the city scale communal institutions articulate broad residential clusters often synonymous with political territories, indicative of spaces of dispute, at the scale of the settlement, the configuration of communal spaces describes and dictates the manner in which these communities interact, organize and define themselves internally. Identity is therefore multi-scalar; a group may present as one ethno-political entity at the scale of the city, it may simultaneously exist as multiple ethno-religious groups at the scale of the settlement. Whilst neither definition negates the other, analysis shows that broad political definitions hide richer, more nuanced definitions of identity that persist at the scale of the settlement

The everyday and the post-disaster urban systems as one thing: A configurational approach to enhance the recovery and resilience of cities affected by tsunamis.

Tsunamis, despite occurring with low frequency, are permanent hazards for a large number of coastal cities and their consequences are highly devastating in terms of human losses, material damages and urban structure disruptions. It is argued in this paper that the urban structure not only has to be recovered after the tsunami event, but also has to provide an important basis for the continuing activities of the city, playing a fundamental role in the resilience of the whole urban system. By adopting a spatio-configurational approach based on space syntax theories and techniques, this research focuses on the dynamics of urban structures in relation to the different scenarios that tsunami-prone cities must face. The urban resilience process in both soon-after tsunami and post-tsunami scenarios is analysed using a Chilean coastal city located in a seismically active region as case study. The resilience capacity of the city in a soon-after tsunami situation is studied focusing on the influence of the urban layout in the route-finding decision makings during the evacuation process. The analysis reveals a weak correspondence between the existing evacuation plan and natural movement patterns, affecting the process of evacuation-route identification and the capacity to rapidly react to the threat. Additionally, the urban resilience in a post-disaster scenario is analysed regarding the ability of the city to maintain the basic functions and structures in order to be able to recover from tsunami impacts. The findings reveal important disruptions in the urban systems spatial organisation, affecting the distribution of urban centralities and changing the operating patterns of the city after tsunami events. From this, the paper develops a comprehensive understanding of the different phases of the tsunami-prone city from a configurational approach, laying the foundations for evidence-based strategic proposals to enhance urban resilience capacity

Understanding the roles of urban configuration on spatial heterogeneity and submarket regionalisation of house price pattern in a mix-scale hedonic model: The case of Shanghai, China

Hedonic model is a powerful tool to investigate the important factors featuring cities' house markets globally; but the development of a local regression approach named as 'Mixed Geographically Weighted Regression' (MGWR) has brought a new insight into urban studies in the field of house price modelling with a proper consideration of spatial heterogeneity, which enables urban planners to know valuable local and global information about elements that factor the property value. In this paper, we proposed a two-step framework to understand the spatial heterogeneity and submarket regionalisation via MGWR in a case study of Shanghai. In the first step, a mixed GWR hedonic model is adopted with the incorporation of globally fixed effect and local factors. In this manner, the influence surface of spatial configuration and land use settings on house price patterns are measured by controlling other elements. Compared with the outputs of ordinary least squares (OLS) analysis and purely local model, the results of specified model in this study are more promising, indicating that the spatial heterogeneity of house price is a complex urban system. In the second stage, a data-driven approach is adopted to detect the spatially homogeneous submarkets based on the coefficients of accessibility indices obtained from MGWR instead of the raw data. Comparison of a regular cluster analysis using housing structural information and the prosed approach is conducted. The results suggest that spatial accessibility and function accessibility are key factors in shaping spatially continuous housing sub-markets on multiple scales with other elements. The findings finally reveal that multi-level modelling procedures provide additional and useful insights into the varying relationships between spatial layouts and the housing price distribution and that urban configuration not only affects house price pattern but also influence shifting housing submarkets

Sketch-a-park Study of the usability of diagrams for participatory sketching

Children’s view in participation currently gaining popularity (CABE Space and CABE Education, 2004) along with digital tools of participation based on design exploration currently known as Digital Participatory Platforms (DPPs) (Falco and Kleinhans, 2018), (Gün et al., 2020). Space Syntax Theory (SST) offers a well-proven human-centred analytic framework with applications for public engagement via digital twins (Dembski et al., 2019). Yet, as some authors argue (Baeck and Saunders, 2015), (Dembski et al., 2020), more needs to be done to improve the experiential side of these systems and empower citizens and children, in particular, to carry out their designs within these events using what is. We argue that using diagrammatic sketching as the basis of DPPs is particularly suited for SST since most SS models work out abstractions of urban morphology which can be drawn using simple diagrammatic sketches. However, this type of drawing may prove too abstract for participants and questions remain open regarding the usability of this type of drawings in a participatory environment. It is yet to be proven whether general members of the public, in particular young kids, can engage with diagrammatic sketches and what influence digital environments have on this engagement. To address these questions, we carried out two pilot studies with participants aged 10 to 11-year-old where we asked them to carry out drawings of urban proposals with different levels of information regarding diagrammatic drawings. Tests were repeated with different groups making paper drawings as well as using a bespoke digital tool at different stages of the drawing. We develop an analytic framework for drawings and carry out a comparative study of the material produced. Results from the experiment suggest that 10- to 11-year-old can easily understand the abstraction behind diagrammatic sketches and adopt this technique as a form of expression. We observe that this happens more markedly when using digital tools. This suggests diagrammatic sketches have the potential to be deployed as part of a SS driven participatory tool

Karachi: The transformation and spatial politics of a Post-colonial migrant city

The partition of the Indian Sub-continent in 1947 resulted in the mass movement of people between India and Pakistan with a number of Urdu-speaking, Muslim communities choosing to re-settle in Karachi, Pakistan. These Muhajir or "refugee" communities have now been resident in the city for over 60 years and whilst the term traditionally means "refugee" in Urdu-their mother-tongue-in the context of Karachi today, it refers specifically to the descendants of these first wave (Partition, 1947) Urdu-speaking migrants from India. The community was initially seen as a landless, rootless people but, over time, they have become one of the key actors in the ethno-political landscape of urban Sindh, in Pakistan today. Whilst the political exploits of this community have been extensively reported and documented by anthropologists and journalist as part of Karachi's tumultuous political history, little has been written about the settlements and spatial practices of this amalgam of diverse, primarily North Indian migrant communities and how their arrival, and occupation has impacted and transformed the manner in which the city has developed. Using space syntax analysis and information drawn from master-plans, urban development reports, historical accounts, and political, religious and linguistic identity-markers associated with the Muhajir community, this study analyses how the city of Karachi has grown and developed through the last 65 years of its post-Partition history and tracks the settlement patterns of the Muhajir community into and around the city. The study shows that, whilst Karachi may be considered a Muhajir city, the community established clusters in very specific areas of the city at the time of their first settlement in the early 1950s and, whilst newer areas have been added to the city, these community-based clusters have persisted and densified over time. The manner in which the community has consolidated and marked its spaces in the city and the way their presence has impacted its growth seems to suggest that the community's identity has gone through a process of transformation and concretisation from Muhajirs as disadvantaged refugees to Muhajirs as a formidable ethnic group with considerable political clout that they exercise with regard to decisions that pertain to the growth and development of the city today

Using space syntax method to train a model for unsupervised detection of socio-economic conditions - the case of metropolitan area of Tehran

The availability of open-source data, coupled with recent advances in technology has made it easier to create large scale urban and regional models used in the field of environmental studies and specifically space syntax. With the use of open data, large scale regional road-centre line models (Turner, 2005) can now be created and processed to explain the spatial configuration as well as the structure of the built environment. While the study of the socio-economic condition of the built environment correlated with the configuration of the space has been the general use of these models, there has been less focus on multi-layered analysis and metrics across a large model. On another hand, with restrictions on datasets from formal resources, the conventional use of space syntax theories and methods are limited. However, incorporating more advanced methods of quantitative analysis, space syntax can compensate for the lack of available formal dataset in reading and/or predicting environmental phenomena. Given that with the available data sources such as Open Street Map, consistent spatial network models are available, RCL segment models can be trained to predict the socio-economic condition of areas where the formal data is not obtainable. This research puts forward a workflow through which, the spatial network model can be used to train a model that predicts mentioned phenomena. This workflow uses a large segment model of the metropolitan area of Tehran and uses the centrality measures from space syntax analysis to train an unsupervised model which can predict possible missing information. It also assesses the efficacy of the model and shows to what extent the model is to be trusted and what the shortcomings of the model are. It is shown that although the models are very efficient in predicting the required conditions there should be a supervised assessment on the parameters of the algorithms to optimize the outcome