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Robust Parameter Design on Dual Stochastic Response Models With Constrained Bayesian Optimization
In engineering system design, minimizing the variations of the quality measurements while guaranteeing their overall quality up to certain levels, namely the robust parameter design (RPD), is crucial. Recent works have dealt with the design of a system whose response-control variables relationship is a deterministic function with a complex shape and function evaluation is expensive. In this work, we propose a Bayesian optimization method for the RPD of stochastic functions. Dual stochastic response models are carefully designed for stochastic functions. The heterogeneous variance of the sample mean is addressed by the predictive mean of the log variance surrogate model in a two-step approach. We establish an acquisition function that favors exploration across the feasible and optimality-improvable regions to effectively and efficiently solve the stochastic constrained optimization problem. Further, the performance of our proposed method is demonstrated by the extensive numerical and case studies. Note to Practitioners-Many manufacturing processes involve undesirable variations, which create variations in the final products. For example, many emerging manufacturing processes, such as nanomanufacturing, involve complex physical and chemical dynamics and transformation, creating variations in the manufacturing output. In such processes, it is crucial to design the manufacturing processes or products so that they have minimum variations in their quality. Meanwhile, it is also important to maintain the overall quality of the designed processes or products. Furthermore, acquiring data from many advanced manufacturing processes is often very costly, especially in the designing stage. In this work, we propose a data-driven method that automatically finds the best setting of manufacturing processes or products with the minimum variations of quality and a given constraint on the average quality satisfied. Our proposed method is used before conducting every experiment; It analyzes the historical data from previous experiments and provides a setting to be used in the next experiment. Our proposed method efficiently utilizes the historical data, and thus finds the best robust setting by conducting only a small number of experiments.
Seawater Desalination Derived Entirely from Ocean Biomass
Solar-driven interfacial evaporation shows great prospects for seawater desalination with its rapid fast evaporation rate and high photothermal conversion efficiency. Here, a sustainable, biodegradable, non-toxic, and highly efficient full ocean biomass-based solar-driven evaporator is reported, which is composed of chitosan (CS) hydrogel as the hydratable skeleton and cuttlefish ink (CI) as the photothermal material. Under solar irradiation, the cuttlefish ink powder harvests solar energy and heats the surrounding water. Simultaneously, the water in the three-dimensional network of chitosan hydrogel is rapidly replenished by the interconnected porous structure and the hydrophilic functional groups attached to the polymer chains. With its enlarged evaporation surface, high solar absorptance, adequate water transportation, good salt drainage, and heat localization, the CI/CS-based evaporator achieves a remarkable evaporation rate of 4.1 kg m-2 h-1 under one sun irradiance (1 kW m-2) with high-quality freshwater yields. This full ocean biomass-based evaporator with abundant raw material availability provides new possibilities for an efficient, stable, sustainable, and environmentally friendly solar evaporator with guaranteed water quality.
Application of the BSRN Data in Validating the GEWEX SRB Data: Quality-Control and Resulting Available Monthly Means
The BSRN data have been used in validation of the satellite-based GEWEX SRB data, and the recent Release 4.0-IP data cover the 34-year period from July 1983 to June 2017. Here we focus on the validation of the shortwave monthly means from 1992 to 2017 against the BSRN Global 1. We first perform the BSRN-recommended quality-control on the original data. We then calculate the monthly-hourly means from which we calculate the monthly means. Twenty-four (24) monthly-hourly means are required to calculate a monthly mean. To guarantee the quality of the monthly mean, we also require that 95% or more hourly means be available in order for a monthly-hourly mean to be calculated. Since the above quality-control significantly reduces the number of available monthly means, we are curious how many monthly means we would get if we relax the quality-control, and how the resulting monthly means would compare with the GEWEX SRB data. In a version we experimented, only constant upper and lower bounds are imposed on various fluxes, and the original data are largely retained. We found that many more monthly means would be available, and the overall bias and RMS would not be significantly different from that of the strict quality-control. With the strict quality-control, if we let Avail (minimum percentage of available hourly means required for a monthly-hourly mean to be computed) change from 3.2% to 95%, the Bias/RMS/N change from -2.77/20.56/9756 to -0.35/13.41/4581, where N is the number of available monthly means, and Bias and RMS are in the unit of W/sq. m. On the other hand, with the lax quality-control, when Avail changes from 3.2% to 95%, the Bias/RMS/N change from -0.82/19.53/9819 to -0.21/14.41/5875. South Pole (SPO) is one of the sites we are particularly interested in. With the strict quality-control, and when Avail changes from 3.2% to 95%, the Bias/RMS/N change from 5.89/15.85/283 to 1.23/5.52/133; with the lax quality-control, the Bias/RMS/N change from 1.17/11.21/284 to 1.88/7.9/177.
All-quad meshing without cleanup
Here, we present an all-quad meshing algorithm for general domains. We start with a strongly balanced quadtree. In contrast to snapping the quadtree corners onto the geometric domain boundaries, we move them away from the geometry. Then we intersect the moved grid with the geometry. The resulting polygons are converted into quads with midpoint subdivision. Moving away avoids creating any flat angles, either at a quadtree corner or at a geometry–quadtree intersection. We are able to handle two-sided domains, and more complex topologies than prior methods. The algorithm is provably correct and robust in practice. It is cleanup-free, meaning we have angle and edge length bounds without the use of any pillowing, swapping, or smoothing. Thus, our simple algorithm is fast and predictable. This paper has better quality bounds, and the algorithm is demonstrated over more complex domains, than our prior version.
Automatic Review of Abstract State Machines by Meta Property Verification
A model review is a validation technique aimed at determining if a model is of sufficient quality and allows defects to be identified early in the system development, reducing the cost of fixing them. In this paper we propose a technique to perform automatic review of Abstract State Machine (ASM) formal specifications. We first detect a family of typical vulnerabilities and defects a developer can introduce during the modeling activity using the ASMs and we express such faults as the violation of meta-properties that guarantee certain quality attributes of the specification. These meta-properties are then mapped to temporal logic formulas and model checked for their violation. As a proof of concept, we also report the result of applying this ASM review process to several specifications.
Effects of Data Quality on the Characterization of Aerosol Properties from Multiple Sensors
Cross-comparison of aerosol properties between ground-based and spaceborne measurements is an important validation technique that helps to investigate the uncertainties of aerosol products acquired using spaceborne sensors. However, it has been shown that even minor differences in the cross-characterization procedure may significantly impact the results of such validation. Of particular consideration is the quality assurance I quality control (QA/QC) information - an auxiliary data indicating a "confidence" level (e.g., Bad, Fair, Good, Excellent, etc.) conferred by the retrieval algorithms on the produced data. Depending on the treatment of available QA/QC information, a cross-characterization procedure has the potential of filtering out invalid data points, such as uncertain or erroneous retrievals, which tend to reduce the credibility of such comparisons. However, under certain circumstances, even high QA/QC values may not fully guarantee the quality of the data. For example, retrievals in proximity of a cloud might be particularly perplexing for an aerosol retrieval algorithm, resulting in an invalid data that, nonetheless, could be assigned a high QA/QC confidence. In this presentation, we will study the effects of several QA/QC parameters on cross-characterization of aerosol properties between the data acquired by multiple spaceborne sensors. We will utilize the Multi-sensor Aerosol Products Sampling System (MAPSS) that provides a consistent platform for multi-sensor comparison, including collocation with measurements acquired by the ground-based Aerosol Robotic Network (AERONET), The multi-sensor spaceborne data analyzed include those acquired by the Terra-MODIS, Aqua-MODIS, Terra-MISR, Aura-OMI, Parasol-POLDER, and CalipsoCALIOP satellite instruments.
Automated Theorem Proving in High-Quality Software Design
The amount and complexity of software developed during the last few years has increased tremendously. In particular, programs are being used more and more in embedded systems (from car-brakes to plant-control). Many of these applications are safety-relevant, i.e. a malfunction of hardware or software can cause severe damage or loss. Tremendous risks are typically present in the area of aviation, (nuclear) power plants or (chemical) plant control. Here, even small problems can lead to thousands of casualties and huge financial losses. Large financial risks also exist when computer systems are used in the area of telecommunication (telephone, electronic commerce) or space exploration. Computer applications in this area are not only subject to safety considerations, but also security issues are important. All these systems must be designed and developed to guarantee high quality with respect to safety and security. Even in an industrial setting which is (or at least should be) aware of the high requirements in Software Engineering, many incidents occur. For example, the Warshaw Airbus crash, was caused by an incomplete requirements specification. Uncontrolled reuse of an Ariane 4 software module was the reason for the Ariane 5 disaster. Some recent incidents in the telecommunication area, like illegal "cloning" of smart-cards of D2GSM handies, or the extraction of (secret) passwords from German T-online users show that also in this area serious flaws can happen. Due to the inherent complexity of computer systems, most authors claim that only a rigorous application of formal methods in all stages of the software life cycle can ensure high quality of the software and lead to real safe and secure systems. In this paper, we will have a look, in how far automated theorem proving can contribute to a more widespread application of formal methods and their tools, and what automated theorem provers (ATPs) must provide in order to be useful.
A Conceptual Design and Economic Assessment of a Chitin Biorefinery Based on Shrimp Processing Wastes
Due to the extensive production of shrimp in captivity, waste generation has increased significantly and has become an environmental problem. The recovery of biomolecules can be an important way to mitigate the environmental problems associated with processing in this sector. In this sense, the present work aimed to evaluate a biorefinery approach for valuing shrimp farming waste to obtain astaxanthin, chitin and chitosan. Stoichiometric segmentation was used as a tool to identify the process steps, whose information on process variables (fresh water consumption, flow rate and reaction conditions) was adapted from the literature. A biorefinery coupled to a shrimp processing plant was proposed for the immediate use of highly perishable biomass, to guarantee the quality of the extracted products and reduce storage and transportation costs. In practice, the biomass treatment sequence adopted (demineralization followed by deproteinization) eliminates the depigmentation step, as the chitin obtained has a lighter tone. The proposed route was evaluated for four scenarios based on two indicators: gross economic potential (EGP) and metrics for inspection of sales and reagents (MISR). The results indicate that economic viability is achieved only for the production of chitosan, resulting in a gross revenue of US$832.50/cycle and a MISR value > 1. The sale of astaxanthin promotes an increase of US$3.73/cycle in the EGP, considered too low for the inclusion of another stage in the process.
Assessing direct and indirect emissions of greenhouse gases in road transportation, taking into account the role of uncertainty in the emissions inventory
Highlights: • The use-chain model implemented in this paper is effective in minimizing uncertainty. • Data integration is important to reduce uncertainty. • An innovative metric, Emission Value at Risk, was used to adjust uncertainty values. • Indirect impacts of economic activities change the estimate of GHG emissions. - Abstract: Greenhouse gas (GHG) concentration in the atmosphere has increased since the beginning of the industrial era, with dramatic effects on climate change. Transportation is one of the main sources of GHGs, with more than two-thirds of transport-related GHG emissions attributable to road vehicles. Any policy that aims to reduce GHG emissions needs robust measuring methods that guarantee the quality and reliability of primary data and estimates. However, these estimates are subject to uncertainty, both at the stage of compiling accounting tables and at the stage of using this information to formulate a specific policy question. This paper considers how to reduce uncertainty in estimating GHG emissions from road transportation, with specific reference to a regional emissions inventory in Italy. We propose the application of a use-chain model that can tackle uncertainty in measuring GHG emissions by enhancing the quality of the emissions data registry in the inventory. This new metric, which we call emission value at risk (VaR), draws from methodologies and concepts employed in the insurance and financial sectors. Moreover, additional assessments are performed, integrating the inventory data with those available in the regional energy balance and disaggregated sectoral economic dataset. The results show that a sound accounting method enables uncertainty in emission data to be taken into account, thus improving the design of appropriate strategies to reduce GHG emissions.
Real-Time Optimization of Distribution-level Energy Resources [SWR-18-27]
Researchers at NREL have developed a novel real-time control architecture to optimize the operation of DERs at residential, commercial, and industrial levels. The real-time system enables (portions of) feeders to emulate virtual power plants providing services to the rest of the grid, while ensuring satisfaction of electrical limits and maximizing customers’ benefits. This system can be integrated with legacy hardware and/or new advanced systems to optimally manage both individually-controlled DERs and aggregations of DERs. By virtue of the proposed engineering approach, the DERs collectively regulate the powers at an electrical point to respond to grid dispatch signals such as an automatic generation control, a ramping signal, or a 5-minute dispatch. Overall, this architecture allows end customers to minimize their payments and partake in grid operations while guaranteeing power quality in the distribution network.
Robust, nonlinear, high angle-of-attack control design for a supermaneuverable vehicle
High angle-of-attack flight control laws are developed for a supermaneuverable fighter aircraft. The methods of dynamic inversion and structured singular value synthesis are combined into an approach which addresses both the nonlinearity and robustness problems of flight at extreme operating conditions. The primary purpose of the dynamic inversion control elements is to linearize the vehicle response across the flight envelope. Structured singular value synthesis is used to design a dynamic controller which provides robust tracking to pilot commands. The resulting control system achieves desired flying qualities and guarantees a large margin of robustness to uncertainties for high angle-of-attack flight conditions. The results of linear simulation and structured singular value stability analysis are presented to demonstrate satisfaction of the design criteria. High fidelity nonlinear simulation results show that the combined dynamics inversion/structured singular value synthesis control law achieves a high level of performance in a realistic environment.
Certification of ICI 1012 optical data storage tape
ICI has developed a unique and novel method of certifying a Terabyte optical tape. The tape quality is guaranteed as a statistical upper limit on the probability of uncorrectable errors. This is called the Corrected Byte Error Rate or CBER. We developed this probabilistic method because of two reasons why error rate cannot be measured directly. Firstly, written data is indelible, so one cannot employ write/read tests such as used for magnetic tape. Secondly, the anticipated error rates need impractically large samples to measure accurately. For example, a rate of 1E-12 implies only one byte in error per tape. The archivability of ICI 1012 Data Storage Tape in general is well characterized and understood. Nevertheless, customers expect performance guarantees to be supported by test results on individual tapes. In particular, they need assurance that data is retrievable after decades in archive. This paper describes the mathematical basis, measurement apparatus and applicability of the certification method.
Efficient Implementation of Artificial Neural Networks for Sensor Data Analysis Based on a Genetic Algorithm
The reliability of many industrial processes depends on the sensor system. However, these sensors can be affected by noise, perturbations and failures. Hence, sensor monitoring and diagnosis are fundamental to guarantee the quality of an industrial process. Nowadays, artificial neural networks (ANN) are widely used in sensor signal processing and diagnosis. However, those ANNs usually require many artificial neurons, being difficult to implement in software and hardware due to their high computational costs. This paper presents an optimized implementation of artificial neurons in ANNs for sensor data analysis using a Genetic Algorithm (GA). The objective of GA is to find an adequate segmentation to reduce the activation function approximation error. One of the advantages of the proposed approach is that the cost function used in GA considers the effect of factors such as the ANN architecture or the number of bits used in arithmetic operations. The proposed ANN implementation technique aims to get the best possible approximation for a specific ANN architecture, making easier its implementation in software and hardware. Simulation and experimental results using FPGA (Field Programmable Gate Array) prove the advantages of the proposed approach for implementing sensor data analysis systems based on ANNs.
Non-conformity Scores for High-Quality Uncertainty Quantification from Conformal Prediction
High-quality uncertainty quantification (UQ) is a critical component of enabling trust in deep learning (DL) models and is especially important if DL models are to be deployed in high-consequence applications. Conformal prediction (CP) methods represent an emerging nonparametric approach for producing UQ that is easily interpretable and, under weak assumptions, provides a guarantee regarding UQ quality. This report describes the research outputs of an Exploratory Express Laboratory Directed Research and Development (LDRD) project at Sandia National Laboratories. This project focused on how best to implement CP methods for DL models. This report introduces new methodology for obtaining high-quality UQ from DL models using CP methods, describes a novel system of assessing UQ quality, and provides experimental results that demonstrate the quality of the new methodology and utility of the UQ quality assessment system. Avenues for future research and discussion of potential impacts at Sandia and in the wider research community are also given.
Technical Note: On the impact of the incident electron beam energy on the primary dose component of flattening filter free photon beams
Purpose: For commercially available linear accelerators (Linacs), the electron energies of flattening filter free (FFF) and flattened (FF) beams are either identical or the electron energy of the FFF beam is increased to match the percentage depth dose curve (PDD) of the FF beam (in reference geometry). This study focuses on the primary dose components of FFF beams for both kinds of settings, studied on the same Linac. Methods: The measurements were conducted on a VersaHD Linac (Elekta, Crawley, UK) for both FF and FFF beams with nominal energies of 6 and 10 MV. In the clinical setting of the VersaHD, the energy of FFF{sub M} (Matched) beams is set to match the PDDs of the FF beams. In contrast the incident electron beam of the FFF{sub U} beam was set to the same energy as for the FF beam. Half value layers (HVLs) and a dual parameter beam quality specifier (DPBQS) were determined. Results: For the 6 MV FFF{sub M} beam, HVL and DPBQS values were very similar compared to those of the 6 MV FF beam, while for the 10 MV FFF{sub M} and FF beams, only %dd(10){sub x} and HVL values were comparable (differences below 1.5%). This shows that matching the PDD at one depth does not guarantee other beam quality dependent parameters to be matched. For FFF{sub U} beams, all investigated beam quality specifiers were significantly different compared to those for FF beams of the same nominal accelerator potential. The DPBQS of the 6 MV FF and FFF{sub M} beams was equal within the measurement uncertainty and was comparable to published data of a machine with similar TPR{sub 20,10} and %dd(10){sub x}. In contrast to that, the DPBQS’s two parameters of the 10 MV FFF{sub M} beam were substantially higher compared to those for the 10 MV FF beam. Conclusions: PDD-matched FF and FFF beams of both nominal accelerator potentials were observed to have similar HVL values, indicating similarity of their primary dose components. Using the DPBQS revealed that the mean attenuation coefficient was found to be the same within the uncertainty of 0.8% for 6 MV FF and 6 MV FFF{sub M} beams, while for 10 MV beams, they differed by 6.4%. This shows that the DPBQS can provide a differentiation of photon beam characteristics that would remain hidden by the use of a single beam quality specifier, such as %dd(10){sub x} or HVL.
Extremum-seeking control for an Ultrasonic/Sonic Driller/Corer (USDC) driven at high-power
Future NASA exploration missions will increasingly require sampling, in-situ analysis and possibly the return of material to Earth for further tests. One of the challenges to addressing this need is the ability to drill using for low axial loading while operating from light weight platforms (e.g., lander, rover, etc.) as well as operate at planets with low gravity. For this purpose, the authors developed the Ultrasonic/Sonic Driller/Corer (USDC) jointly with Cybersonics Inc. Studies of the operation of the USDC at high power have shown there is a critical need to self-tune to maintain the operation of the piezoelectric actuator at resonance. Performing such tuning is encountered with difficulties and to address them an extremum-seeking control algorithm is being investigated. This algorithm is designed to tune the driving frequency of a time-varying resonating actuator subjected to both random and high-power impulsive noise disturbances. Using this algorithm the performance of the actuator is monitored on a time-scale that is compatible with its slowly time-varying physical characteristics. The algorithm includes a parameter estimator, which estimates the coefficients of a function that characterizes the quality factor of the USDC. Since the parameter estimator converges sufficiently faster than the time-varying drift of the USDC's physical parameters, the proposed extremum-seeking estimation and control algorithm is potentially applicable for use as a closed-loop health monitoring system. Specifically, this system may be programmed to automatically adjust the duty-cycle of the sinusoidal driver signal to guarantee that the quality factor of the USDC does not fall below a user-defined set-point. Such fault-tolerant functionality is especially important in automated drilling applications where it is essential not to inadvertently drive the piezoelectric ceramic crystals of the USDC beyond their capacities. The details of the algorithm and experimental results will be described and discussed in this paper.
In-situ X-Ray Analysis of Rapid Thermal Processing for Thin-Film Solar Cells: Closing the Gap between Production and Laboratory Efficiency
For materials synthesis, it is well known that the material final state may not reach equilibrium and depends on the synthetic process. In particular, processes that quickly remove the available energy from the material may leave it in a metastable state and the metastability may actually impart desirable functional properties. By its very nature, Rapid thermal processing (RTP) is ideally suited to produce such metastable materials. However, metastability and the dynamics of reaching a metastable state are poorly understood, since this is best accomplished through in situ monitoring. In this regard, RTP is particularly challenging as the processing time are very short (seconds to minutes). As a result, there is only poor understanding, and hence use, of RTP in industry. This is potentially a cost-increasing limitation, because RTP can decrease cost by decreasing processing time, and as such, increase throughput and decrease the total thermal budget of processing - a significant cost. RTP is already being used for key processing steps in PV technologies. With silicon wafer PV, it is used for establishing electrical contact between the Ag metal grid and the silicon (known as firing). In this process, a silicon wafer with deposited metal/frit in a grid pattern is heated rapidly to temperatures between 750 and 800 ºC. The processing time when the temperature is held above 600ºC is short (<5 seconds). This process has historically been optimized empirically and it is unclear how the thermal processing affects formation of the final contact between the metal and the silicon. In the case of thin-film PV, RTP has been demonstrated in the process of making absorber layers, i.e. CIGS and CZTS. Use of RTP can reduce the processing time from 10s of minutes to seconds, reducing the thermal budget and increasing the throughput significantly. The conversion from precursor material to final PV material is not well understood, and most of the process optimization is done empirically. Again, the proposed in situ monitoring will provide insight into the conversion process. We have developed a unique instrument for in situ monitoring of the reaction process during RTP. The most fundamental property to monitor is the atomic arrangement (for solids, crystalline structure) and thus we have focused on this property. The chamber was designed to collect X-ray diffraction (XRD) for crystal phase determination, although it has lent insight in the formation of liquids. We designed and constructed both inert (air) and reactive (S/Se) versions of this chamber. We have applied the RTP-XRD methodology to: silicon solar cell electrical contact formation; the reaction sequence for forming CIGS PV thin films from copper selenide and indium gallium selenide precursors; the phase sequence for forming HC(NH2)2PbI3 (FAPbI3) and CH3NH3PbI3 (MAPbI3) hybrid-perovskite PV thin films. The RTP instrument enables real-time collection of X-ray diffraction data with intervals as short as 100 ms, and while heating at ramp rates as high 100 ºCs-1 up to 1200 ºC. The system is portable and can be installed on a synchrotron beamline. The RTP reactor consists of a metallic body (front cap assembly, central block and end cap assembly) that houses a quartz reaction chamber. The sample is secured inside the reaction chamber on a sample holder connected to the front-cap assembly. Modifications of the chamber were made for safely handling sulfur and selenium vapor environments. A Se/S source holder was added to generate a Se/S over pressure in the chamber on heating and the entrance window is made wider in order to accommodate the detachable additional holder. Se/S are toxic in nature and therefore a proper Se/S trapping is used before releasing the gases to exhaust. Screen-printing provides an economically attractive means for making Ag electrical contacts to Si solar cells, but the use of Ag substantiates a significant manufacturing cost, and the glass frit used in the paste to enable contact formation contains Pb. To achieve optimal electrical performance and to develop pastes with alternative, abundant, and non-toxic materials requires understanding the contact formation process during firing. We use the RTP-XRD chamber during firing of Ag-Si contacts to reveal the reaction sequence for contact formation. The findings show that between 500 ºC and 650 ºC PbO in the frit etches the SiNx antireflective-coating on the solar cell, exposing the Si surface. Then, above 650 ºC, Ag+ dissolves into the molten glass frit – key for enabling deposition of metallic Ag on the emitter surface and precipitation of Ag nanocrystals within the glass. This clarifies contact formation mechanisms and can be used to suggest approaches for development of inexpensive, nontoxic solar cell contacting pastes. We used the RTP/XRD chamber to study the formation of CuInGaS/Se (CIGS) PV films by in-situ selenization of pre-deposited metal stacks and annealing of pre-deposited Cu-In-Ga-Se precursors. During the metal stack selenization, we observed that Se first reacts with the metals and forms selenides. We observed formation of intermetallics such as Cu2In and binary selenides during heating. On further annealing in a Se atmosphere, CuInSe2 and CuGaSe2 forms which on heating up to 550 °C reacts further to form the CIGS phase. On prolonged exposure to 550 °C for more than 5 mins or higher temperature, we see separation into Ga-rich and Ga-depleted CIGS phases. On introducing a holding step at 400 °C for 10 min during the annealing ramp, the CIGS phase (forms between 500-550 °C), appears to be less prone to decomposition into high-Ga and low-Ga phases during holding at peak temperature. Lead halide perovskites have emerged as successful optoelectronic materials with high photovoltaic power conversion efficiencies and low material cost. However, substantial challenges remain in the scalability, stability and fundamental understanding of the materials. We demonstrated the application of radiative thermal annealing, an easily scalable processing method, for synthesizing formamidinium lead iodide (FAPbI3) perovskite solar absorbers. Devices fabricated from films formed via radiative thermal annealing have equivalent efficiencies to those annealed using a conventional hotplate. By coupling results from in situ x-ray diffraction using a radiative thermal annealing system with device performances, we mapped the processing phase space of FAPbI3 and corresponding device efficiencies. Our map of processing-structure-performance space suggests the commonly used FAPbI3 annealing time, 10 min at 170 °C, can be significantly reduced to 40 s at 170 °C without affecting the photovoltaic performance. Applying the Johnson-Mehl-Avrami model to the decomposition into PbI2, the activation energy was determined. We also presented a well-controlled, manufacturing relevant annealing method, radiative thermal annealing, for the methylammonium lead triiodide films formed by solvent engineering process, with dimethylformamide (DMF) and dimethyl sulfoxide as solvent and diethyl ether as the antisolvent. Radiative thermal annealing can produce high quality perovskite films, evidenced by high efficiency solar cell devices, in a shorter time than the widely-used hotplate annealing. Using in-situ x-ray diffraction during the radiative annealing, we show that the role of the antisolvent is not to form an intermediate compound (a methylammonium iodide, lead iodide, and dimethyl sulfoxide compound) by washing of the main solvent (DMF) but to achieve a pin-hole free, uniform film of methylammonium lead iodide. We find that having the intermediate compound does not guarantee a high quality (pin-hole free) perovskite film. Our study was extended to reveal the effect of annealing environment, annealing temperature profile, and deposition substrate.