Reading Through a Plan

Problem: Planners may read plans often, but the profession continues to view the interpretation of plan content as something that is either too obvious or too unimportant to require explicit discussion. Plans are seldom adequately interpreted. This is regrettable because plans contain a rich variety of content and meaning.

Purpose: This article calls for planners to “read through” plans, not just to grasp their essential ideas or the means of implementing those ideas, but also to perceive additional levels of meaning relating to a) a plan's place within a larger intellectual sphere, b) a plan's statement on the social and political values of the time, and c) a plan as a part of the history of the planning profession and the life of cities.

Methods: I propose a visual approach to plan reading descended from Panofsky's (1939 Panofsky, E. 1939. Studies in iconology: Humanistic themes in the art of the Renaissance, New York, NY: Harper and Row.  [Google Scholar]) theory of iconology and use this to examine three very different plans that describe different size cities (small, large, very large) during different periods over the past 80 years (the 1930s, 1960s, 2000s). I analyze three levels of meaning in each plan: its factual meaning, or “plain sense” (Mandelbaum, 1990 Mandelbaum, S. J. 1990. Reading plans. Journal of the American Planning Association, 56(3): 350–358. [Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]); its contextual meaning, or relation to political, social, economic, and physical conditions; and its temporal meaning, or setting within the scope of observations made by other plan readers in the perspective of elapsed time.

Results and conclusions: Factual readings show that information may be found in diverse aspects of a plan document, from seemingly superficial aspects like its cover to unarguably central elements such as recommendations. Factual readings depend on understanding the relationships among different elements, and reveal information about the plan and its framers that may not otherwise be readily apparent. Contextual readings show us that plan recommendations are as much a product of contemporary conditions and norms as they are of plan-specific “survey and diagnosis” (Nolen, 1936 Nolen, J. 1936. Comprehensive city plan for Dubuque, Iowa, Dubuque, IA: City Planning and Zoning Commission.  [Google Scholar]). This raises the question of whether plan quality is to be judged only in terms of skillful execution of concerns of the day or whether innovation is also important. Temporal readings reveal that plans and planning have changed dramatically over time, simultaneously confirming and questioning the conventional wisdom of planning history.

Takeaway for practice: Many planners read plans on a regular basis, and plans continue to constitute the major printed currency of the planning profession. Both plans and planning will benefit if planners become more discerning readers of the profession's principal idea vessels. Formal plan interpretation is rare, but each planner can become a better plan interpreter.

Research support: None.     

Uncertainty quantification via bayesian inference using sequential monte carlo methods for CO2 adsorption process

This work presents the uncertainty quantification, which includes parametric inference along with uncertainty propagation, for CO₂ adsorption in a hollow fiber sorbent, a complex dynamic chemical process. Parametric inference via Bayesian approach is performed using Sequential Monte Carlo, a completely parallel algorithm, and the predictions are obtained by propagating the posterior distribution through the model. The presence of residual variability in the observed data and model inadequacy often present a significant challenge in performing the parametric inference. In this work, residual variability in the observed data is handled by three different approaches: (a) by performing inference with isolated data sets, (b) by increasing the uncertainty in model parameters, and finally, (c) by using a model discrepancy term to account for the uncertainty. The pros and cons of each of the three approaches are illustrated along with the predicted distributions of CO₂ breakthrough capacity for a scaled‐up process. © 2016 American Institute of Chemical Engineers AIChE J, 62: 3352–3368, 2016     

Scaling Effects in Perovskite Ferroelectrics: Fundamental Limits and Process‐Structure‐Property Relations

Ferroelectric materials are well‐suited for a variety of applications because they can offer a combination of high performance and scaled integration. Examples of note include piezoelectrics to transform between electrical and mechanical energies, capacitors used to store charge, electro‐optic devices, and nonvolatile memory storage. Accordingly, they are widely used as sensors, actuators, energy storage, and memory components, ultrasonic devices, and in consumer electronics products. Because these functional properties arise from a noncentrosymmetric crystal structure with spontaneous strain and a permanent electric dipole, the properties depend upon physical and electrical boundary conditions, and consequently, physical dimension. The change in properties with decreasing physical dimension is commonly referred to as a size effect. In thin films, size effects are widely observed, whereas in bulk ceramics, changes in properties from the values of large‐grained specimens is most notable in samples with grain sizes below several micrometers. It is important to note that ferroelectricity typically persists to length scales of about 10 nm, but below this point is often absent. Despite the stability of ferroelectricity for dimensions greater than ~10 nm, the dielectric and piezoelectric coefficients of scaled ferroelectrics are suppressed relative to their bulk counterparts, in some cases by changes up to 80%. The loss of extrinsic contributions (domain and phase boundary motion) to the electromechanical response accounts for much of this suppression. In this article, the current understanding of the underlying mechanisms for this behavior in perovskite ferroelectrics is reviewed. We focus on the intrinsic limits of ferroelectric response, the roles of electrical and mechanical boundary conditions, grain size and thickness effects, and extraneous effects related to processing. In many cases, multiple mechanisms combine to produce the observed scaling effects.     

Aggregate effects and measuring regional dynamics

Empirical models of regional adjustment often control for aggregate effects when estimating the impact of region-specific shocks on local economies. It is, however, difficult to filter out the effects of aggregate shocks—such as oil shocks, uncertainty shocks, or national recessions—because the incidence of these shocks varies across space and time. We propose an improved econometric method to control for this form of spatiotemporal heterogeneity, thereby yielding more accurate estimation of the effects of local shocks on regional economies. Applying the method to US states, we find that labour demand shocks are mostly absorbed through changes in participation; the migration response to these shocks is limited; and recoveries are highly protracted     

Discrete-time contraction constrained nonlinear model predictive control using graph-based geodesic computation

Modern chemical processes need to operate around time-varying operating conditions to optimize plant economy, in response to dynamic supply chains (e.g., time-varying specifications of product and energy costs). As such, the process control system needs to handle a wide range of operating conditions whilst optimizing system performance and ensuring stability during transitions. This article presents a reference-flexible nonlinear model predictive control approach using contraction based constraints. Firstly, a contraction condition that ensures convergence to any feasible state trajectories or setpoints is constructed. This condition is then imposed as a constraint on the optimization problem for model predictive control with a general (typically economic) cost function, utilizing Riemannian weighted graphs and shortest path techniques. The result is a reference flexible and fast optimal controller that can trade-off between the rate of target trajectory convergence and economic benefit (away from the desired process objective). The proposed approach is illustrated by a simulation study on a CSTR control problem.     

Enhanced calcium–magnesium–aluminosilicate (CMAS) resistance of GdAlO3 (GAP) for composite thermal barrier coatings

The impact of calcium–magnesium–alumino-silicate (CMAS) degradation is a critical factor for development of new thermal and environmental barrier coatings. Several methods of preventing damage have been explored in the literature, with formation of an infiltration inhibiting reaction layer generally given the most attention. Gd₂Zr₂O₇ (GZO) exemplifies this reaction with the rapid precipitation of apatite when in contact with CMAS. The present study compares the CMAS behavior of GZO to an alternative thermal barrier coating (TBC) material, GdAlO₃ (GAP), which possesses high temperature phase stability through its melting point as well as a significantly higher toughness compared with GZO. The UCSB laboratory CMAS (35CaO–10MgO–7Al₂O₃–48SiO₂) was utilized to explore equilibrium behavior with 50:50 mol% TBC:CMAS ratios at 1200, 1300, and 1400°C for various times. In addition, 8 and 35 mg/cm² CMAS surface exposures were performed at 1425°C on dense pellets of each material to evaluate the infiltration and reaction in a more dynamic test. In the equilibrium tests, it was found that GAP appears to dissolve slower than GZO while producing an equivalent or higher amount of pore blocking apatite. In addition, GAP induces the intrinsic crystallization of the CMAS into a gehlenite phase, due in part to the participation of the Al₂O₃ from GAP. In surface exposures, GAP experienced a substantially thinner reaction zone compared with GZO after 10 h (87 ± 10 vs. 138 ± 4 μm) and a lack of strong sensitivity to CMAS loading when tested at 35 mg/cm² after 10 h (85 ± 13 versus 246 ± 10 μm). The smaller reaction zone, loading agnostic behavior, and intrinsic crystallization of the glass suggest this material warrants further evaluation as a potential CMAS barrier and inclusion into composite TBCs.     

Fragmentation and granular transition of ceramics for high rate loading

The paper presents a numerical model to study the transition of brittle materials from a cracked solid to a granular medium under impact loading. The model addresses competitive crack coalescence in the transition regime and provides insight into the onset of comminution and the initial conditions for subsequent granular flow. Crack statistics obtained from initial flaws using a wing crack growth-based damage model have been used to discretely model elliptical cracks in three dimensions. These discrete cracks are either generated randomly in space or with a constraint that minimizes the intersection between neighboring cracks. These cracks are then allowed to coalesce with nearby cracks along with favorable directions and the output fragment statistics are predicted. A simple statistical model is proposed that suggests a transition criterion resembling the one obtained from the numerical model. Initial fragments are power-law distributed similarly to experimental observations and particle-based models. A generalized form of a microstructure-dependent granular transition criterion based on a threshold measure of crack lengths has been proposed. This model can be implemented in numerical codes to activate granular physics and calibrate the initial conditions of granular flow, such as fragment size and morphology.     

Insights into the industrial growth of cyanobacteria from a model of the carbon‐concentrating mechanism

With the advent of modern bioengineering tools, photosynthetic organisms are increasingly being engineered to produce chemicals from CO₂ sources, thereby creating a potential route of sustainable chemical production. Cyanobacteria have evolved a carbon‐concentrating mechanism (CCM) that enables growth at low‐environmental carbon concentrations. However at high‐carbon concentrations these benefits may not outweigh synthesis costs. Here, mass transport and kinetic modeling analyses were performed on two species of cyanobacteria as well as a hypothetical no‐CCM mutant. Modeling results correlated with published experimental data. Three conclusions were drawn from the analysis. Carboxysome geometry was unimportant due to the fast relative rate of diffusion of carbon species. Interspecies variations were largely due to active transporters. The no‐carboxysome cell approaches the wild‐type at 10% CO₂. Therefore, in high CO₂ environments the carboxysome and active bicarbonate transporters provide no benefit and a metabolic advantage could be achieved by eliminating the energy‐intensive CCM proteins. © 2014 American Institute of Chemical Engineers AIChE J, 60: 1269–1277, 2014