1) The document discusses uncertainties in differential spectral response (DSR) measurements according to approximations defined in IEC 60904-8.
2) It analyzes the impact of using simplified DSR measurement procedures compared to the complete DSR procedure, through simulations and measurements of non-linear crystalline silicon solar cells.
3) The results show deviations below 5% for all approximations in simulations, and below 1% for measurements when using multicolor bias light ramps.
Modeling and Optimization of Cold Crucible Furnaces for Melting MetalsFluxtrol Inc.
http://fluxtrol.com
Cold Crucible Furnaces (CCFs), widely used in multiple special applications of
melting metals, oxides, glasses and other materials [1], are essentially 3D devices and their modeling is a complicated task. Multiple studies of CCFs have been made for their
optimization, but their electrical efficiency is still low; for metals approximately 25-30% andeven lower. Fluxtrol, Inc., made an extensive study of electromagnetic processes of CCFs using computer simulation and laboratory tests. This study showed that electrical efficiency of CCFs may be strongly improved by means of optimal design of the whole system with use of magnetic flux controllers. Theoretical results had been confirmed by laboratory tests on mockups and by industrial tests with real melting processes. The presentation contains a description of the computer modeling procedure and major findings. They form a basis for optimal design of electromagnetic systems of CCFs.
2014 PV Performance Modeling Workshop: Results from Flash Testing at Multiple Irradiance and Temperatures across Five Photovoltaic Testing Labs: Junaid Fatehi, Yingli Green Energy Americas
Modeling and Optimization of Cold Crucible Furnaces for Melting MetalsFluxtrol Inc.
http://fluxtrol.com
Cold Crucible Furnaces (CCFs), widely used in multiple special applications of
melting metals, oxides, glasses and other materials [1], are essentially 3D devices and their modeling is a complicated task. Multiple studies of CCFs have been made for their
optimization, but their electrical efficiency is still low; for metals approximately 25-30% andeven lower. Fluxtrol, Inc., made an extensive study of electromagnetic processes of CCFs using computer simulation and laboratory tests. This study showed that electrical efficiency of CCFs may be strongly improved by means of optimal design of the whole system with use of magnetic flux controllers. Theoretical results had been confirmed by laboratory tests on mockups and by industrial tests with real melting processes. The presentation contains a description of the computer modeling procedure and major findings. They form a basis for optimal design of electromagnetic systems of CCFs.
2014 PV Performance Modeling Workshop: Results from Flash Testing at Multiple Irradiance and Temperatures across Five Photovoltaic Testing Labs: Junaid Fatehi, Yingli Green Energy Americas
Data Teknis Gossen Metrawatt Ground Tester : GEOHM PRO & GEOHM XTRAPT. Siwali Swantika
Pemesanan produk, hubungi PT Siwali Swantika melalui WhatsApp, Jakarta : 0811-1519-949 (chat only) | Surabaya : 0811-1519-948 (chat only). Kunjungi website kami di www.siwali.com, untuk detail informasi spesifikasi dan model alat.
First results from the full-scale prototype for the Fluorescence detector Arr...Toshihiro FUJII
The Fluorescence detector Array of Single-pixel Telescopes (FAST) is a design concept for the next generation of ultrahigh-energy cosmic ray (UHECR) observatories, addressing the requirements for a large-area, low-cost detector suitable for measuring the properties of the highest energy cosmic rays. In the FAST design, a large field of view is covered by a few pixels at the focal plane of a mirror or Fresnel lens. Motivated by the successful detection of UHECRs using a prototype comprised of a single 200 mm photomultiplier-tube and a 1 m2 Fresnel lens system [Astropart.Phys. 74 (2016) 64-72], we have developed a new full-scale prototype consisting of four 200 mm photomultiplier-tubes at the focus of a segmented mirror of 1.6 m in diameter. In October 2016 we installed the full-scale prototype at the Telescope Array site in central Utah, USA, and began steady data taking. We report on first results of the full-scale FAST prototype, including measurements of artificial light sources, distant ultraviolet lasers, and UHECRs.
35th International Cosmic Ray Conference — ICRC2017 18th July, 2017
Bexco, Busan, Korea
TISSUE PHANTOM RATIO - THE PHOTON BEAM QUALITY INDEXVictor Ekpo
TPR(20,10) is the recommended photon beam quality index by IAEA TRS-398 for megavoltage clinical photons generated by linear accelerators. This presentation goes through the basics of Tissue Phantom Ratio (TPR).
A simulator to reproduce fast rise-up noises which are generated when switching ON / OFF electric current on the inductive load.
It can be used for performance evaluation of electronic equipment upon reproduction of line noises which are intruded to the power supply lines or induced noises onto the telecommunication lines.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
UiPath Test Automation using UiPath Test Suite series, part 4DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 4. In this session, we will cover Test Manager overview along with SAP heatmap.
The UiPath Test Manager overview with SAP heatmap webinar offers a concise yet comprehensive exploration of the role of a Test Manager within SAP environments, coupled with the utilization of heatmaps for effective testing strategies.
Participants will gain insights into the responsibilities, challenges, and best practices associated with test management in SAP projects. Additionally, the webinar delves into the significance of heatmaps as a visual aid for identifying testing priorities, areas of risk, and resource allocation within SAP landscapes. Through this session, attendees can expect to enhance their understanding of test management principles while learning practical approaches to optimize testing processes in SAP environments using heatmap visualization techniques
What will you get from this session?
1. Insights into SAP testing best practices
2. Heatmap utilization for testing
3. Optimization of testing processes
4. Demo
Topics covered:
Execution from the test manager
Orchestrator execution result
Defect reporting
SAP heatmap example with demo
Speaker:
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Epistemic Interaction - tuning interfaces to provide information for AI supportAlan Dix
Paper presented at SYNERGY workshop at AVI 2024, Genoa, Italy. 3rd June 2024
https://alandix.com/academic/papers/synergy2024-epistemic/
As machine learning integrates deeper into human-computer interactions, the concept of epistemic interaction emerges, aiming to refine these interactions to enhance system adaptability. This approach encourages minor, intentional adjustments in user behaviour to enrich the data available for system learning. This paper introduces epistemic interaction within the context of human-system communication, illustrating how deliberate interaction design can improve system understanding and adaptation. Through concrete examples, we demonstrate the potential of epistemic interaction to significantly advance human-computer interaction by leveraging intuitive human communication strategies to inform system design and functionality, offering a novel pathway for enriching user-system engagements.
State of ICS and IoT Cyber Threat Landscape Report 2024 previewPrayukth K V
The IoT and OT threat landscape report has been prepared by the Threat Research Team at Sectrio using data from Sectrio, cyber threat intelligence farming facilities spread across over 85 cities around the world. In addition, Sectrio also runs AI-based advanced threat and payload engagement facilities that serve as sinks to attract and engage sophisticated threat actors, and newer malware including new variants and latent threats that are at an earlier stage of development.
The latest edition of the OT/ICS and IoT security Threat Landscape Report 2024 also covers:
State of global ICS asset and network exposure
Sectoral targets and attacks as well as the cost of ransom
Global APT activity, AI usage, actor and tactic profiles, and implications
Rise in volumes of AI-powered cyberattacks
Major cyber events in 2024
Malware and malicious payload trends
Cyberattack types and targets
Vulnerability exploit attempts on CVEs
Attacks on counties – USA
Expansion of bot farms – how, where, and why
In-depth analysis of the cyber threat landscape across North America, South America, Europe, APAC, and the Middle East
Why are attacks on smart factories rising?
Cyber risk predictions
Axis of attacks – Europe
Systemic attacks in the Middle East
Download the full report from here:
https://sectrio.com/resources/ot-threat-landscape-reports/sectrio-releases-ot-ics-and-iot-security-threat-landscape-report-2024/
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
GraphRAG is All You need? LLM & Knowledge GraphGuy Korland
Guy Korland, CEO and Co-founder of FalkorDB, will review two articles on the integration of language models with knowledge graphs.
1. Unifying Large Language Models and Knowledge Graphs: A Roadmap.
https://arxiv.org/abs/2306.08302
2. Microsoft Research's GraphRAG paper and a review paper on various uses of knowledge graphs:
https://www.microsoft.com/en-us/research/blog/graphrag-unlocking-llm-discovery-on-narrative-private-data/
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
Elevating Tactical DDD Patterns Through Object CalisthenicsDorra BARTAGUIZ
After immersing yourself in the blue book and its red counterpart, attending DDD-focused conferences, and applying tactical patterns, you're left with a crucial question: How do I ensure my design is effective? Tactical patterns within Domain-Driven Design (DDD) serve as guiding principles for creating clear and manageable domain models. However, achieving success with these patterns requires additional guidance. Interestingly, we've observed that a set of constraints initially designed for training purposes remarkably aligns with effective pattern implementation, offering a more ‘mechanical’ approach. Let's explore together how Object Calisthenics can elevate the design of your tactical DDD patterns, offering concrete help for those venturing into DDD for the first time!
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Are you looking to streamline your workflows and boost your projects’ efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, you’re in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Here’s what you’ll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
We’ll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Don’t miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Essentials of Automations: Optimizing FME Workflows with Parameters
20 supsi workshop schinke
1. Uncertainty of DSR
measurements according to
approximations defined in the
IEC 60904-8 standard
K. Bothe, D. Hinken and C. Schinke
Calibration and Test Center Solar Cells
Institute for Solar Energy Research
SUPSI-Workshop, Photoclass Project (4/2017)
2. DSR system at ISFH CalTeC
• Grating monochromator:
280 to 1200nm in 10nm steps
• 48 bias lamps, bias current up to
14A for large-area solar cells
• Three transimpedance amplifiers
(small: 250mA, large: 14A, Vmon)
• Two light fields:
50x50mm² and 160x160mm²
• Motorized axis for reference and
sample cells
• Sample Temperatures from 20 to
40°C (determination of TC)
• ISO 17025 accredited by DAkkS
since 2016
3. Measurement procedure
• Calibration of monochromatic light and bias light (Ebias) using a WPVS
reference solar cell
• DSR measurement of device under test at various (usually 8) bias levels:
10, 100, 200, 400, 600, 800, 1000 and 1100 W/m²
• Integration over Ebias
• Calculation of relative sstc-curves, sstc.rel(l) and mismatch correction factor
• Determination of ISTC at sun simulator
• Scaling of DSR curves and sstc.rel(l) using ISTC
• Difference to PTB approach (previous talk by I. Kröger): Integration is not
carried out over Ibias since only relative (unscaled) DSR values are
measured
4. Measurement uncertainty
• Monte-Carlo uncertainty analysis with 12 uncertainty components:
fdist: Height-difference of reference and DUT
fwlshift: Deviation in wavelength of monochromatic light
fbandwidth: Bandwidth of monochromatic light
fTRef: Temperature difference to 25°C of reference
fTDUT: Temperature difference to 25°C of DUT
fcellinhom: Impact of light inhomogeneity on cells with current collection inhomogeneity
frepRef: Reproducibility of measurement of reference
frepDUT: Reproducibility of measurement of DUT
fscale: Uncertainty of Isc from IV measurement
fnonlin: Non-linearity of transimpedance amplifier
fref: Uncertainty of primary normal
fhom: Reproducibility of inhomogeneity correction
DUT meas dist nonlin wlshift bandwidth TRef TDUT scale cellinhom repRef repDUT ref homs s f f f f f f f f f f f / f % %
5. Comparison to PTB:
WPVS reference solar cell
• WPVS reference solar cell
• Fixed bias intensity/current
• Curves of PTB (black) and
ISFH-CalTeC (red)
• Enavg = 0.1
6. Solar Cell Calibration Standards
F. D‘Amore, Solar standards and certification, www.med-desire.eu, 2015
7. IEC 60904-8 Ed. 3.0
F. D‘Amore, Solar standards and certification, www.med-desire.eu, 2015
8. IEC 60904-8 Ed. 3.0
F. D‘Amore, Solar standards and certification, www.med-desire.eu, 2015
Required for spectral
mismatch correction
9. IEC 60904-8 Ed. 3.0
complete DSR procedure
Definition of the requirements for the measurement of the spectral responsivity of
linear and non-linear photovoltaic devices:
For highest accuracy, the differential spectral responsivity 𝑠 𝜆, 𝐼bias has to be
measured under at least 5 different bias light irradiances resulting in short
circuit currents 𝐼SC between 5% and 110% of the short circuit current under
standard test conditions 𝐼SC.STC. The spectral responsivity 𝑠STC 𝜆 is calculated
by integrating over 𝐼bias.
complete differential spectral responsivity (DSR) procedure
10. IEC 60904-8 Ed. 3.0
simplifications
• Simplifications aiming at determining one or more appropriate bias
irradiances 𝐸0 at which the measured differential spectral responsivity best
approximates the spectral responsivity
1. bias ramps at 3 to 5 wavelength 𝜆 𝑛 with step width of 200nm increasing
the bias light irradiance in 3 to 5 steps corresponding to 𝐼bias between 5%
and 110% of 𝐼SC.STC
multicolor bias ramps
2. use of white light instead of monochromatic light
white bias ramp
3. bias irradiance 𝐸0 resulting in a bias current 𝐼bias between 30% to 40% of
𝐼SC.STC
30% to 40% bias
4. bias irradiance 𝐸0 resulting in a bias current 𝐼bias of 10% of 𝐼SC.STC if
linearity is proven by showing that the differential spectral responsivity
does not change by more than 2% when measuring at bias light
intensities corresponding to 5% and 15% 𝐼SC.STC
(not considered: only non-linear cells analyzed here)
11. IEC 60904-8 Ed. 3.0
simplifications
• Simplifications aiming at determining one or more appropriate bias
irradiances 𝐸0 at which the measured differential spectral responsivity best
approximates the spectral responsivity
1. bias ramps at 3 to 5 wavelength 𝜆 𝑛 with step width of 200nm increasing
the bias light irradiance in 3 to 5 steps corresponding to 𝐼bias between 5%
and 110% of 𝐼SC.STC
multicolor bias ramps
2. use of white light instead of monochromatic light
white bias ramp
3. bias irradiance 𝐸0 resulting in a bias current 𝐼bias between 30% to 40% of
𝐼SC.STC
30% to 40% bias
4. bias irradiance 𝐸0 resulting in a bias current 𝐼bias of 10% of 𝐼SC.STC if
linearity is proven by showing that the differential spectral responsivity
does not change by more than 2% when measuring at bias light
intensities corresponding to 5% and 15% 𝐼SC.STC
(not considered: only non-linear cells analyzed here)
9-25 (+1)
3-5 (+1)
1
3
no.ofmeasurements
12. Deviations of simplifications compared
to complete DSR procedure
1. Simulation of the DSR of a non-linear c-Si solar cell and analysis according
to the complete DSR procedure as well as simplifications 1 to 3
2. Measurement of the DSR of a non-linear c-Si solar cell and analysis
according to the complete DSR procedure as well as simplifications 1 to 3
13. Simulation approach
Wavelength [nm]
400 600 800 1000 1200
Measureddifferential
spectralresponsivitys[mA/Wm
2
]
0.0
0.2
0.4
0.6
0.8
900 950 1000 1050 1100
0.4
0.5
0.6
0.7
0,10,25 & 50
W/m
2
100
200
300
400
600-1200
SR
~
Bias intensity [W/m2
]
0 200 400 600 800 1000
Differentialsandintegrated
spectralresponsivitys[mA/Wm
2
]
0.0
0.2
0.4
0.6
0.8
300nm
500nm
1100nm
700nm
900nm
286 317
305
bias ramp
~
s~
s
p-type Cz Si
τSRH,n0 = 80 µs
τSRH,p0 = 800 µs
J0r,c = 790 fA/cm²
J0e = 59 fA/cm²
SiOSn = 1.22×104 cm/s
Sp = 5.92 cm/s
• FEM simulation of a PERC c-Si solar
cell using SENTAURUS DEVICE
• Silicon dioxide dielectric layer at the
rear side with very high interface
defect density of 3×1010 cm-2
• 𝑠 𝜆, 𝐸bias curves show high non-
linearity
• Bias ramps at different wavelengths
yield bias intensity setpoints E0 from
286 to 317 W/m²
14. Impact of bias ramp wavelength
and bias irradiance
• How much do the simplifications
deviate from the complete DSR
method?
• Simplification 1 (Multicolor bias ramps):
Deviations below -1.3%
• Simplification 2 (White bias ramp):
Deviations below 4.6%
• Simplification 3 (30% bias):
Deviations below 3.9%
Wavelength [nm]
200 400 600 800 1000 1200
DeviationofsfromsSTC[%]
-2
-1
0
1
2
3
4
5
bias intensity
fixed bias irradiance
E0=300 W/m
2
white bias ramp
E0=304 W/m
2
multicolor ramp
adjusted bias irradiance
~
15. Measurement
Wavelength [nm]
400 600 800 1000 1200
Measureddifferential
spectralresponsivitys[mA/Wm
2
]
0.00
0.01
0.02
0.03
0.04
0.05
800 900 1000 1100
0.30
0.35
0.40
0.45
0.50
10 W/m
2
100
20
200
900
1100
~
Bias intensity [W/m2
]
0 200 400 600 800 1000 1200
Differentialsandintegrated
spectralresponsivitys[mA/Wm
2
]
0.01
0.02
0.03
0.04
0.05
300nm
500nm
1100nm
700nm
900nm
E0=287 301
s
bias ramp
~
s~
Si3N4
p-type Cz Si
• p-type Cz Si without AlOx but with SiN
• 𝑠 𝜆, 𝐸bias curves show high non-
linearity
• Bias ramps at different wavelengths
yield bias intensity setpoints from 287
to 301 W/m²
(Simulation: 286 – 317 W/m²)
17. Summary
• Analysis of non-linear c-Si solar cell (simulation and measurement).
• Deviations below 5% were determined from solar cell device
simulations for all approximations.
• Simplification 1 (Multicolor-biasramps) was the most robust approach
(deviations below 1.3%).
• Simplification 2 (White-biasramp) showed deviations below 4.6%.
• Simplification 3 (30% bias) showed deviations below 3.9%.
• For non-linear solar cells: Use the complete DSR procedure if
possible.
• If a simplification is required, use the multicolor-biasramps approach if
possible.
Thank you for your attention!