Automated computational design method for energy systems in buildings using capacity and operation optimization

Abstract A Framework of computational design method and model is proposed for layout and geometry design of complicated mechanical systems, which is named “configuration network and its viewing control”. In the method, a design object is represented with a set of declarative relationships among various elements of a system, that is, configurations, which is gradually extended from schematic structure to exact layout and geometry through design process. Since a whole of such configurations forms a too complicated network to compute all together, how to view subparts is controlled based on levels of granularity and width of scope range. Such a configuration network is made to grow and refined through embodying geometry and layout corresponding to a focused subpart with a numerical optimization procedure. The framework has also an ability to flexibly integrate with engineering analysis. Moreover, a design system is implemented with an object-oriented programming technique, and it is applied to a design problem of air conditioner units in order to show the validity and effectiveness of the framework.

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Computational Design for Digitally Fabricated 3D Inductive Power Transfer Coils

Journal of Computing and Information Science in Engineering ◽

10.1115/1.4053500 ◽

2022 ◽

pp. 1-28

Author(s):

Jun Xu ◽

Eugeni L. Doubrovski ◽

Jo Geraedts ◽

Yu Song

Keyword(s):

Design Method ◽

Computational Design ◽

Future Research ◽

Receiver Coil ◽

Power Transfer ◽

Coil Design ◽

Optimal Position ◽

Inductive Power Transfer ◽

Transmitter Coil ◽

Inductive Power

Abstract The geometric shapes and the relative position of coils influence the performance of a three-dimensional (3D) inductive power transfer system. In this paper, we propose a coil design method for specifying the positions and the shapes of a pair of coils to transmit the desired power in 3D. Given region of interests (ROIs) for designing the transmitter and the receiver coils on two surfaces, the transmitter coil is generated around the center of its ROI first. The center of the receiver coil is estimated as a random seed position in the corresponding 3D surface. At this position, we use the heatmap method with electromagnetic constraints to iteratively extend the coil until the desired power can be transferred via the set of coils. In each step, the shape of the extension, i.e. a new turn of the receiver coil, is found as a spiral curve based on the convex hulls of adjacent turns in the 2D projection plane along their normal direction. Then, the optimal position of the receiver coil is found by maximizing the efficiency of the system. In the next step, the position and the shape of the transmitter coil are optimized based on the fixed receiver coil using the same method. This zig-zag optimization process iterates until an optimum is reached. Simulations and experiments with digitally fabricated prototypes were conducted and the effectiveness of the proposed 3D coil design method was verified. Possible future research directions are highlighted well.

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Multistate design of influenza antibodies improves affinity and breadth against seasonal viruses

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1806004116 ◽

2019 ◽

Vol 116 (5) ◽

pp. 1597-1602 ◽

Cited By ~ 11

Author(s):

Alexander M. Sevy ◽

Nicholas C. Wu ◽

Iuliia M. Gilchuk ◽

Erica H. Parrish ◽

Sebastian Burger ◽

...

Keyword(s):

Electrostatic Interactions ◽

Design Method ◽

Computational Design ◽

Surface Proteins ◽

Antigenic Drift ◽

Global Public Health ◽

Large Panels ◽

Rapid Changes ◽

Large Panel ◽

Ha Protein

Influenza is a yearly threat to global public health. Rapid changes in influenza surface proteins resulting from antigenic drift and shift events make it difficult to readily identify antibodies with broadly neutralizing activity against different influenza subtypes with high frequency, specifically antibodies targeting the receptor binding domain (RBD) on influenza HA protein. We developed an optimized computational design method that is able to optimize an antibody for recognition of large panels of antigens. To demonstrate the utility of this multistate design method, we used it to redesign an antiinfluenza antibody against a large panel of more than 500 seasonal HA antigens of the H1 subtype. As a proof of concept, we tested this method on a variety of known antiinfluenza antibodies and identified those that could be improved computationally. We generated redesigned variants of antibody C05 to the HA RBD and experimentally characterized variants that exhibited improved breadth and affinity against our panel. C05 mutants exhibited improved affinity for three of the subtypes used in design by stabilizing the CDRH3 loop and creating favorable electrostatic interactions with the antigen. These mutants possess increased breadth and affinity of binding while maintaining high-affinity binding to existing targets, surpassing a major limitation up to this point.

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Designing Optimal Origami Structures by Computational Evolutionary Embryogeny

Volume 5B: 38th Mechanisms and Robotics Conference ◽

10.1115/detc2014-34377 ◽

2014 ◽

Author(s):

Wei Li ◽

Daniel A. McAdams

Keyword(s):

Design Method ◽

Center Of Mass ◽

Computational Design ◽

Design Methods ◽

Performance Criteria ◽

Pattern Design ◽

Modern Computer ◽

Evolutionary Operators ◽

Origami Engineering ◽

Profile Position

As the advantages of foldable or deployable structures are being discovered, research into origami engineering has attracted more focus from both artists and engineers. With the aid of modern computer techniques, some computational origami design methods have been developed. Most of these methods focus on the problem of origami crease pattern design — the problem of determining a crease pattern to realize a specified origami final shape, but don’t provide computational solutions to actually developing a shape that meets some design performance criteria. This paper presents a design method that includes the computational design of the finished shape as well as the crease pattern. The origami shape will be designed to satisfy geometric, functional, and foldability requirements. This design method is named computational evolutionary embryogeny for optimal origami design (CEEFOOD), which is an extension of the genetic algorithm (GA) and an original computational evolutionary embryogeny (CEE). Unlike existing origami crease pattern design methods that adopt deductive logic, CEEFOOD implements an abductive approach to progressively evolve an optimal design. This paper presents how CEEFOOD — as a member of the GA family — determines the genetic representation (genotype) of candidate solutions, the formulation of the objective function, and the design of evolutionary operators. This paper gives an origami design problem, which has requirements on the folded-state profile, position of center of mass, and number of creases. Several solutions derived by CEEFOOD are listed and compared to highlight the effectiveness of this abductive design method.

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A cloud-based operation optimization of building energy systems using a hierarchical multi-agent control

Journal of Physics Conference Series ◽

10.1088/1742-6596/1343/1/012053 ◽

2019 ◽

Vol 1343 ◽

pp. 012053

Author(s):

Alexander Kümpel ◽

Thomas Storek ◽

Marc Baranski ◽

Markus Schumacher ◽

Dirk Müller

Keyword(s):

Energy Systems ◽

Building Energy ◽

Operation Optimization ◽

Building Energy Systems ◽

Multi Agent ◽

Agent Control

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Toward the computational design of protein crystals with improved resolution

Acta Crystallographica Section D Structural Biology ◽

10.1107/s2059798319013226 ◽

2019 ◽

Vol 75 (11) ◽

pp. 1015-1027 ◽

Cited By ~ 2

Author(s):

Jeliazko R. Jeliazkov ◽

Aaron C. Robinson ◽

Bertrand García-Moreno E. ◽

James M. Berger ◽

Jeffrey J. Gray

Keyword(s):

Weak Interactions ◽

Design Method ◽

Point Mutations ◽

Computational Design ◽

Data Bank ◽

Protein Crystals ◽

Single Individual ◽

Space Group ◽

Protein Backbones ◽

Crystal Space

Substantial advances have been made in the computational design of protein interfaces over the last 20 years. However, the interfaces targeted by design have typically been stable and high-affinity. Here, we report the development of a generic computational design method to stabilize the weak interactions at crystallographic interfaces. Initially, we analyzed structures reported in the Protein Data Bank to determine whether crystals with more stable interfaces result in higher resolution structures. We found that for 22 variants of a single protein crystallized by a single individual, the Rosetta-calculated `crystal score' correlates with the reported diffraction resolution. We next developed and tested a computational design protocol, seeking to identify point mutations that would improve resolution in a highly stable variant of staphylococcal nuclease (SNase). Using a protocol based on fixed protein backbones, only one of the 11 initial designs crystallized, indicating modeling inaccuracies and forcing us to re-evaluate our strategy. To compensate for slight changes in the local backbone and side-chain environment, we subsequently designed on an ensemble of minimally perturbed protein backbones. Using this strategy, four of the seven designed proteins crystallized. By collecting diffraction data from multiple crystals per design and solving crystal structures, we found that the designed crystals improved the resolution modestly and in unpredictable ways, including altering the crystal space group. Post hoc, in silico analysis of the three observed space groups for SNase showed that the native space group was the lowest scoring for four of six variants (including the wild type), but that resolution did not correlate with crystal score, as it did in the preliminary results. Collectively, our results show that calculated crystal scores can correlate with reported resolution, but that the correlation is absent when the problem is inverted. This outcome suggests that more comprehensive modeling of the crystallographic state is necessary to design high-resolution protein crystals from poorly diffracting crystals.

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Computational Simulations of the Anterior Vertebral Surface for Optimal Surgical Instrumentation Design

Journal of Medical Devices ◽

10.1115/1.3439667 ◽

2010 ◽

Vol 4 (2) ◽

Cited By ~ 2

Author(s):

Francisco Casesnoves

Keyword(s):

Vertebral Body ◽

Design Method ◽

Computational Design ◽

Human Bone ◽

Mechanical Forces ◽

Grid Data ◽

Statistical Parameters ◽

Surgical Instrumentation ◽

The Individual ◽

Fitting Model

The engineering design of surgical instrumentation to apply mechanical forces and linear moments on the human bones during the operations constitutes a rather difficult task. This is due both to the natural and pathological irregularities of the human bone morphology and surfaces and also to the individual variations from one patient to another. Usually, the forces are applied by the surgeon only on a determined part of the bone surfaces. This paper describes an innovative computational design method to digitalize, simulate, and fit mathematically the anterior vertebral body facet. We used real experimental data from 17 human cadaveric specimens to get and store a large amount of numerical surface digital values. The complete anterior vertebral body side was visualized and analyzed with grid data Subroutine, which was also used first to select the so-called natural regions of interest (ROIs). These ROIs correspond to those parts of the surface in contact with the surgical instrumentation, where the mechanical forces are applied. Subsequently, a numerical mathematical fitting-model was implemented for these ROIs. This was carried out with the development of a 3D geometrical least-squares optimization algorithm and appropriate software designed according to the proper numerical method selected. In doing so, the 3D superficies equations of the anterior vertebral body (L3, L4, L5, and S1) were determined after these fittings were mathematically checked as appropriate. Statistical parameters and determination coefficients that define the error boundaries and the goodness of this optimal fitting-model were calculated and NURBS error data in similar studies were commented. It was proven that the principal source of error was the micro- and macro-irregularities of human bone facets. The final surface equations, and their geodesics, were used to obtain accurate data for the spinal surgery instrumentation manufacturing. The industrial bioengineering result was the application of these equations for the design of a new spinal vertebral surgical distractor. This innovative distractor separates two adjacent vertebrae while keeping them parallel. That is, at their natural inclination, avoiding hammering the vertebrae to make the intervertebral space wider. The device mechanics also minimizes the necessary force to be carried out by the surgeon during the operation.

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Daily Operation Optimization of a Hybrid Energy System Considering a Short-Term Electricity Price Forecast Scheme

Energies ◽

10.3390/en12050924 ◽

2019 ◽

Vol 12 (5) ◽

pp. 924 ◽

Cited By ~ 2

Author(s):

Pedro Bento ◽

Hugo Nunes ◽

José Pombo ◽

Maria Calado ◽

Sílvio Mariano

Keyword(s):

Energy Systems ◽

Energy System ◽

Short Term ◽

Operation Optimization ◽

Hybrid Energy ◽

Price Forecast ◽

Hybrid Energy Systems ◽

The Cost ◽

Transportation Electrification ◽

Installed Capacity

The scenario where the renewable generation penetration is steadily on the rise in an increasingly atomized system, with much of the installed capacity “sitting” on a distribution level, is in clear contrast with the “old paradigm” of a natural oligopoly formed by vertical structures. Thereby, the fading of the classical producer–consumer division to a broader prosumer “concept” is fostered. This crucial transition will tackle environmental harms associated with conventional energy sources, especially in this age where a greater concern regarding sustainability and environmental protection exists. The “smoothness” of this transition from a reliable conventional generation mix to a more volatile and “parti-colored" one will be particularly challenging, given escalating electricity demands arising from transportation electrification and proliferation of demand-response mechanisms. In this foreseeable framework, proper Hybrid Energy Systems sizing, and operation strategies will be crucial to dictate the electric power system’s contribution to the “green” agenda. This paper presents an optimal power dispatch strategy for grid-connected/off-grid hybrid energy systems with storage capabilities. The Short-Term Price Forecast information as an important decision-making tool for market players will guide the cost side dispatch strategy, alongside with the storage availability. Different scenarios were examined to highlight the effectiveness of the proposed approach.

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