Design Tradeoffs Research Articles

Finite key performance of satellite quantum key distribution under practical constraints

Global-scale quantum communication networks will require efficient long-distance distribution of quantum signals. While optical fibre communications are range-limited due to exponential losses in the absence of quantum memories and repeaters, satellites enable intercontinental quantum communications. However, the design of satellite quantum key distribution (SatQKD) systems has unique challenges over terrestrial networks. The typical approach to modelling SatQKD has been to estimate performances with a fully optimised protocol parameter space and with few payload and platform resource limitations. Here, we analyse how practical constraints affect the performance of SatQKD for the Bennett-Brassard 1984 (BB84) weak coherent pulse decoy state protocol with finite key size effects. We consider engineering limitations and trade-offs in mission design including limited in-orbit tunability, quantum random number generation rates and storage, and source intensity uncertainty. We quantify practical SatQKD performance limits to determine the long-term key generation capacity and provide performance benchmarks to support the design of upcoming missions.

Mean-square convergent continuous state estimation of randomly switched linear systems with unobservable subsystems and stochastic output noises

This paper studies mean-square (MS) convergent observers for estimating continuous states of randomly switched linear systems (RSLSs) with unobservable subsystems that are subject to stochastic output observation noises. When subsystems are unobservable and switching sequences are random, the classical Kalman–Bucy filters that are applied to observable sub-states are shown to be potentially divergent. It is also shown that unless the switching interval T can be selected to be sufficiently small from the outset, MS convergence may never be achieved, regardless of how the observers for the subsystems are designed. The critical threshold Tmax on T is derived for MS convergent observers to be achievable. Under the condition T<Tmax, this paper introduces design algorithms for subsystem observers to generate a globally MS convergent observer for the entire continuous state. A fundamental design tradeoff between convergence speeds and steady-state estimation errors is analyzed. This paper extends our recent new framework and algorithms for strong convergent observer design in RSLSs by including observation noises, considering multi-output systems, establishing new algorithms for MS convergence, and developing design tradeoff analysis. Examples and a practical case study are presented to illustrate the design procedures, main convergence properties, and error analysis.

Computer-Aided Time-Domain Operation and Design Optimization of Resonant Converters

This paper presents a method for computer-aided operation and design optimization of resonant converters using time domain analysis. Resonant converters can operate in different operation stage trajectories (OSTs) with the change of two degrees of freedom (2DOFs), namely switching frequency <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">f_s</i> and duty ratio <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">d</i> . The paper calculates and analyzes the operation characteristics, zero voltage switching-on (ZVS-on), and zero current switching-off (ZCS-off) regions when the 2DOFs vary by solving the OST differential equation sets. Based on this analysis, an algorithm is proposed to find the operation and design optimizations of a specific resonant converter while considering 2DOFs by traversing all possible control coordinates. The paper provides several case studies to demonstrate the design trade-offs in different scenarios, which are verified through experimental verifications.

Solar-Assisted Monetization of Municipal Solid Waste

Municipal solid waste (MSW) is a significant resource, especially for biomass-based monetization. In addition to its economic potential, it can also provide an effective pathway for decarbonization in the energy and chemical sectors. In this work, MSW monetization is coupled with the solar-assisted generation of “green” hydrogen and oxygen via electrolysis. The dual utilization of electrolysis-produced hydrogen and oxygen offers several advantages, including the reduction in the carbon footprint, the tunability of the characteristics of synthesis gas (syngas) to conform to the values needed for the manufacture of various chemicals, and the reduction in the overall cost compared to systems focusing on hydrogen generation only. A superstructure is developed to represent the configurations of interest and serve as a basis for formulating an optimization program that can be solved to identify the optimal design and operating strategies. A multi-period optimization formulation is developed to identify the maximum profit subject to the various modeling equations and constraints. The environmental considerations are addressed using the ɛ-constraint method by iteratively varying carbon footprint cuts. A case study is solved for the City of Jeddah, and the results assess the tradeoffs of various design and operating strategies, their impact on profitability, and their environmental impact.

Current Sensor Integration Issues with Wide-Bandgap Power Converters.

Precise current sensing is essential for several power electronics' protection, control, and reliability mechanisms. Even so, WBG power converters will likely struggle to develop a single current-sensing scheme to measure various types of currents due to the limited space and size of these devices, the required high sensing speed, and the high electromagnetic interference (EMI) emissions they cause. Analysis of existing current sensors was conducted in such terms with the objective of understanding the challenges associated with their integration into WBG power converters. Since each of these requirements has different design tradeoffs, it is challenging to consider one specific method of current sensing to be perfect for all situations; thus, the possibility of developing novel methods to improve the performance of these single-scheme current sensors is further explored.

A framework for evaluating inherent biases within ship design tools

In early-stage design, critical decisions must be made within a limited information environment. Designers conduct and interpret analyses, taking into account any associated decision risks, with the hopes of making meaningful design trade-offs. To aid in this, synthesis tools are often utilized to generate potential solutions to enable one to characterize the desired design space. While previous research has demonstrated that solutions are prescribed by the tools that generate them, there seems to be little research toward determining the impact of these predispositions on the quality of solutions relative to the intended outcome. To make truly informed decisions, designers must be able to assess a tool’s inherent biases, its intended applications, and its contextual appropriateness to the design questions that it is being used to answer. Currently, this inability can promote inaccurate perspectives of the desired design space, can negatively impact the ultimate success of the design, and poses a currently unquantified risk within the design process.This paper presents a framework for evaluating the inherent biases within a ship design synthesis tool. A genetic algorithm was developed to generate ensembles of solutions associated with a given design tool. The Parent–Child Network, derived from the dynamics within the genetic algorithm, was developed to capture causal relationships between solutions over time. The algorithm was modified to impose designer-determined biases on the solution generation process for the purpose of creating multiple data sets that enable comparative assessments of their resultant quality. This newly developed approach is used to establish the comparative context necessary for a model’s biases to be analyzed and understood by creating a reference and biasing cases. Two aspects of quality, solution-centric and generative, are defined, and a variety of solution-centric and generative analyses are developed to evaluate a tool’s inherent tendencies. A comprehensive case study was conducted to demonstrate implementing the framework and interpreting the analyses. The case study’s results demonstrate that the framework can successfully identify a model’s biases, providing designers with the contextual information necessary to make truly informed decisions.

Gradient-Based Trade-Off Design for Engineering Applications

The goal of the trade-off design method presented in this study is to achieve newly targeted performance requirements by modifying the current values of the design variables. The trade-off design problem is formulated in the framework of Sequential Quadratic Programming. The method is computationally efficient as it is gradient-based, which, however, requires the performance functions to be differentiable. A new equation to calculate the scale factor to control the size of the design variables is introduced in this study, which can ensure the new design achieves the targeted performance objective. Three formal approaches are developed in this study for trade-off design to handle various design scenarios, which include one that can handle cases with linearly dependent constraints and with more constraints than the number of design variables. Three engineering design problems are presented as examples to validate and demonstrate the use of these trade-off approaches to find the best way to adjust the design variables to meet the revised performance requirements.

SENECA: building a fully digital neuromorphic processor, design trade-offs and challenges.

Neuromorphic processors aim to emulate the biological principles of the brain to achieve high efficiency with low power consumption. However, the lack of flexibility in most neuromorphic architecture designs results in significant performance loss and inefficient memory usage when mapping various neural network algorithms. This paper proposes SENECA, a digital neuromorphic architecture that balances the trade-offs between flexibility and efficiency using a hierarchical-controlling system. A SENECA core contains two controllers, a flexible controller (RISC-V) and an optimized controller (Loop Buffer). This flexible computational pipeline allows for deploying efficient mapping for various neural networks, on-device learning, and pre-post processing algorithms. The hierarchical-controlling system introduced in SENECA makes it one of the most efficient neuromorphic processors, along with a higher level of programmability. This paper discusses the trade-offs in digital neuromorphic processor design, explains the SENECA architecture, and provides detailed experimental results when deploying various algorithms on the SENECA platform. The experimental results show that the proposed architecture improves energy and area efficiency and illustrates the effect of various trade-offs in algorithm design. A SENECA core consumes 0.47 mm2 when synthesized in the GF-22 nm technology node and consumes around 2.8 pJ per synaptic operation. SENECA architecture scales up by connecting many cores with a network-on-chip. The SENECA platform and the tools used in this project are freely available for academic research upon request.

Freeform bending tool design for rectangular profiles and its influence on the process

Abstract Freeform bending offers a wide range of possibilities in terms of component geometries, material grades and profile cross-sections. In the field of circular solid and hollow profiles, the design of the tool is determined by the circular shape of the profile used. When using rectangular profiles, the cross-section of the tool cannot be easily obtained by an offset of the profile cross-section. The large tolerance ranges of the profile standards require compromises with regard to the shape and tolerances of the tool. Tests have shown that the design of the tool has a great influence on the quality of the component. Furthermore, the trade-off in the tool design can lead to unsuitable tool shapes leading to defects and damages on the profile. These are mainly wrinkling, cross-sectional deformations and strongly deformed profile corners, which in some cases form cracks in the material. In this paper, the influences of the tool design on the bending result and the defects of the profiles are investigated. For this purpose, several tool designs with different variants and combinations of the movable die and the fixed die are compared with each other.

Performance of NeRF and its optimized models on generating images from 2D to 3D of animation or game character

Neural Radiance Fields (NeRF) has recently emerged as a promising approach for single-image 3D scene reconstruction. Despite this, most studies on NeRF have focused on real-world data or items with established camera projection connections, rather than snapshots of video game characters that may not have a distinct camera projection connection. Although some research has been conducted on the use of animatable mannequins, the majority of these studies have used photographs of real people as their data source. To date, there has been limited research into the use of NeRF for animation or game characters. In this paper, we compare and evaluate a range of NeRF models on a dataset of animated game characters. The models considered include original NeRF, Block-NeRF, Mip-NeRF, and Pixel-NeRF, each of which has its own design choices and trade-offs. Our results show that Mip-NeRF models are effective at generating high-quality images of game characters on our dataset, while Pixel-NeRF performs poorly on our dataset. Despite these findings, our research demonstrates the feasibility of using NeRF-based models to create realistic character models or animations for video games, with potential applications in game development and virtual reality.

Inertial Stable Platforms for Precision Pointing of Optical Systems in Aerospace Applications

Both airborne and space-based high-energy laser weapon systems present interesting challenges for precision line-of-sight control. Sub-microradian to microradian pointing accuracies are required against dynamic targets. In addition, “absolute” pointing and accurate inertial angular rate measurement are required to support mission requirements. This paper addresses these unique directed-energy weapon (DEW) precision-pointing requirements and their associated implementation alternatives in the context of strapdown and stable platform inertial reference technologies. The contributions of this paper consider the broader issues of DEW requirement drivers, integration of the stabilization system with the rest of the optical system, and design tradeoffs between stable platform and strapdown stabilization mechanizations. Both types of mechanisms are mounted to the gimbal of an imaging system using gryo sensors (gyros) and accelerometers to maintain a desired orientation in inertial space independent of the craft motion. Although both can include an optical reference that propagates through the optical path for optical alignment and jitter control, only in the stable platform is the optical reference stabilized. When combined on the same platform with a stabilized inertial measurement system and closed-loop stabilization with the optical reference, the mechanism becomes a stabilized inertial reference unit, which provides a stabilized optical reference to the electro-optical/laser pointing and jitter control systems.

In Defense of Diversity in Theory-Building Approaches

The complexity of organizations and myriad ways in which they engage with their environments necessitates using our entire arsenal of approaches to theory-building. We respond to Arend's (2023) commentary on Chen, Elfenbein, Posen, and Wang (2023), in which he questions the appropriateness of computational models and critiques our model for delivering too little realism. Building on prior work in this journal, we argue that all theory-building approaches embody trade-offs across generalizability, simplicity, and accuracy. Because of these trade-offs, a diversity in theory-building approaches is required, and attempts to circumscribe theory-development methods should be rejected. We examine two additional aspects of Arend’s commentary. First, we disagree with the claim that computational models are the right tool only “when data do not exist.” This claim confuses the theory-building purpose of computational models with the theory-testing purpose of empirical analysis. Second, we point out that computational and analytical methods are merely different ways to solve formal models, made necessary by differing trade-offs in model design. While our field benefits from criticism and debates, proscribing certain theory-development approaches is unlikely to improve management scholarship. We encourage scholars to continue to use computational models to broaden our perspectives on the complex phenomena in management scholarship.

MRVs: Enforcing Numeric Invariants in Parallel Updates to Hotspots with Randomized Splitting

Performance of transactional systems is degraded by update hotspots as conflicts lead to waiting and wasted work. This is particularly challenging in emerging large-scale database systems, as latency increases the probability of conflicts, state-of-the-art lock-based mitigations are not available, and most alternatives provide only weak consistency and cannot enforce lower bound invariants. We address this challenge with Multi-Record Values (MRVs), a technique that can be layered on existing database systems and that uses randomization to split and access numeric values in multiple records such that the probability of conflict can be made arbitrarily small. The only coordination needed is the underlying transactional system, meaning it retains existing isolation guarantees. The proposal is tested on five different systems ranging from DBx1000 (scale-up) to MySQL GR and a cloud-native NewSQL system (scale-out). The experiments explore design and configuration trade-offs and, with the TPC-C and STAMP Vacation benchmarks, demonstrate improved throughput and reduced abort rates when compared to alternatives.

Design Trade-Off Between Torque Density and Power Factor in Surface-Mounted PM Vernier Machines Through Closed-Form Per-Unit Equations

Benefited from flux modulation effects, surface-mounted permanent magnet vernier machines (SPMVMs) present the high-torque low-speed properties, which can become the potential candidates for direct-drive applications. However, their power factor is inferior to conventional PM machines due to the large inductance caused by parasitic no-working harmonics. This paper is devoted to propose some design considerations of SPMVMs to make a good compromise between torque density and power factor. Via constructing closed-from per-unit equations, the cross-coupling influences of slot/pole combinations and normalized geometric variables on machine performances are revealed. It is found that there is a tradeoff between torque density and power factor. The high magnet thickness to air-gap length ratio is beneficial to decrease inductance, while the flux modulation effect under the large equivalent air-gap length would be impaired. Moreover, the pole-pair ratio, i.e., the PM pole-pair to armature winding pole-pair, should be carefully selected, where the SPMVMs with high pole-pair ratio have the relatively high magnetic loading owing to the strong flux modulation effects, whereas they suffer from the low power factor due to serious harmonic leakage inductance. In particular, taking the end-winding length into consideration, the high torque advantages of high pole-pair ratio SPMVMs under the same copper losses can be well performed with high length-radius ratio. Combined with the analysis, the preferable selections of critical parameters to satisfy various technical indexes are determined. Then, the general design approach is proposed, and two design examples are built and compared. Meanwhile, finite element analysis (FEA) and prototype experiments are carried out to verify the feasibility.

A Millimeter-Wave Three-Way Doherty Power Amplifier for 5G NR OFDM

This article presents a millimeter-wave (mmWave) three-way Doherty output network and its silicon implementation at 38 GHz for 5G new radio (NR) orthogonal frequency-division multiplexing (OFDM). The proposed network synthesis methodology can realize impedance levels that are close to the ideal three-way Doherty operation, reduce the impedance transformation ratio at back-off, and directly absorb the device’s parasitic capacitance. Its design procedure and tradeoffs are discussed in detail. A 38-GHz power amplifier (PA) prototype is implemented in the GlobalFoundries 45-nm CMOS SOI process, achieving 13.7%/11.0% power-added efficiency (PAE) at the 9.5-/11.5-dB back-off, which is among the highest compared with recently reported silicon PAs operating at 35 GHz and above. Tested under 1-and 2-component carrier (CC) 5G NR FR2 64-QAM OFDM signals in the Band n260, the PA demonstrates state-of-the-art average output power (11.3 dBm) and average efficiency (14.7%) with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula> 25-dB error vector magnitude (EVM). The design robustness and reliability are further demonstrated through the testing of multiple samples and PA lifetime.

Millimeter-Wave Receiver With Non-Uniform Time-Approximation Filter

This article presents a non-uniform (NU) time-approximation filter (TAF) technique for a wireless receiver (RX) to reject unwanted blockers. The proposed NU TAF leverages the alias-spreading property of NU sampling (NUS) and a TAF that approximates a finite impulse response (FIR) filter response in the time domain, achieving an overall flexible filter response with a higher attenuation factor. The filter response can be readily reconfigured by changing the NU sequence and/or the TAF waveform without adjusting the passive component value. In addition, a quad-switch gated integrator is proposed to significantly reduce the power consumption by sharing the current among the <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\textit{G} _m$</tex-math> </inline-formula> cells. Detailed theoretical analysis on NU-TAF operation and RX implementation considering circuit non-idealities are provided to explore the design tradeoffs of the proposed techniques. A proof-of-concept millimeter-wave RX is implemented in the 28-nm CMOS process. Thanks to the NU TAF, the RX prototype achieves <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$&gt;$</tex-math> </inline-formula> 45-dB blocker rejection with a 33.7-GHz carrier frequency. The EVM measures <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$-$</tex-math> </inline-formula> 30.9 dB using a 100-MSymbol/s 64-QAM signal in the presence of a 10-dBc out-of-band (OOB) blocker.

A Comprehensive Design and Experiment of a Biplane Quadrotor Tail-Sitter UAV

Tail-sitter unmanned aerial vehicles (UAVs) are promising vertical takeoff and landing (VTOL) UAV suitable for multi-missions but the road to the commercialization of tail-sitter UAVs is tortuous. This paper aims to provide a systematic design methodology and present the development process for a novel biplane quadrotor tail-sitter UAV platform named TW10 to accelerate commercialization of this type of UAV. All the design choices and trade-offs in aerodynamics, structure, avionics, and the control scheme are detailed. A simulation and real flight test results are demonstrated to prove the feasibility of our design methodology. TW10 can carry a 1 kg mission load to achieve more than 2.5 h of flight time. This work serves as a meaningful reference for the promotion of tail-sitter UAVs in practical industrial applications.

Design and Implementation of Fast and Cost-Effective FPGA-Based Fuzzy Rainbow Tradeoffs

Design and Implementation of Fast and Cost-Effective FPGA-Based Fuzzy Rainbow Tradeoffs

Design tradeoffs between traditional hexagonal and emerging cubic InXGa(1–X)N/GaN-based green light-emitting diodes

Here, we report on the design tradeoffs between traditional hexagonal and emerging cubic InXGa(1−X)N/GaN-based green (520nm≤λ≤550nm) light-emitting diodes with special emphasis on the electron blocking layer, number of quantum wells, and thicknesses of quantum wells and barriers. We identified three crucial design rules for cubic green light-emitting diodes: (1) no need for an electron blocking layer; (2) use of a wide quantum well; and (3) choice of thin quantum barriers in multi-quantum well light-emitting diode designs. These design rules increase the internal quantum efficiency of cubic green light-emitting diodes by ∼30.5% under 100A/cm2 injection with respect to traditional designs. Overall, the design rules of cubic light-emitting diodes and their differentiating nature from the traditional, hexagonal ones are crucial for the advent of next-generation cubic light-emitting diodes.

Rapid multi-criterial design of microwave components with robustness analysis by means of knowledge-based surrogates

Manufacturing tolerances and uncertainties concerning material parameters, e.g., operating conditions or substrate permittivity are detrimental to characteristics of microwave components. The knowledge of relations between acceptable parameter deviations (not leading to violation of design specifications) and the nominal performance (not considering uncertainties), and is therefore indispensable. This paper proposes a multi-objective optimization technique of microwave components with tolerance analysis. The goal is to identify a set of trade-off designs: nominal performance versus robustness (quantified by the maximum input tolerance values that allow for achieving 100-percent fabrication yield). Our approach exploits knowledge-driven regression predictors rendered using characteristic points (features) of the component’s response for a rapid evaluation of statistical performance figures, along with trust-region algorithm to enable low execution cost as well as convergence. The proposed methodology is verified with the use of three microstrip circuits, a broadband filter, and two branch-line couplers (a single- and a dual-band one). It is demonstrated that a Pareto set w.r.t. nominal performance and robustness objectives can be produced using only 40 to 60 EM simulations of the respective structure (per design). Reliability of the proposed algorithm is corroborated with the use of EM-based Monte Carlo simulation.