Episode 60 : Pinch Diagram and Heat Integration
The optimal allocation of mass and energy within a unit operation, process and/or site.
Optimal allocation can be based on economic, environmental or other important objectives.
SAJJAD KHUDHUR ABBAS
Ceo , Founder & Head of SHacademy
Chemical Engineering , Al-Muthanna University, Iraq
Oil & Gas Safety and Health Professional – OSHACADEMY
Trainer of Trainers (TOT) - Canadian Center of Human
Development
SimScale teams up with Greenlite, a provider of regulatory and building analysis services, to explore how cloud-based CFD software can be used by engineers and architects to quickly and accurately calculate wind pressure coefficients for projects in the built environment. Importing simulation files into IES and thermal modeling tools gives designers an extra advantage to evaluate ventilation and possible overheating.
comparative analysis of pid and narma l2 controllers for shell and tube heat...INFOGAIN PUBLICATION
The application of this paper firstly simplified mathematical model for heat exchanger process has been developed and used for the dynamic analysis and control design. A conventional PID controller and Advanced Artificial Neural Network NARMA L2 Controller for Shell and Tube heat exchanger is proposed to control the cold water outlet temperature and test the best efficiency of NARMA L2 and PID controller.The control problem formulated as outlet cold water temperature is controlled variable and the inlet hot water temperature is manipulated variable the minimum possible time irrespective of load and process disturbances.Simulation and verified the mathematical model of the controller has been done in MATLAB Simulink. From the simulation results the prime controller has been chosen by comparing the criteria of the response such as settling time, rise time, percentage of overshoot and steady state error.The Neural NetworkNARMA L2 controller is founded to give finest performance for Shell and Heat exchanger problem like temperature control. Later Need to compare Conventional PID and Advance Artificial Neural NetworkNARMA L2 Controller results which lead to decide which one is best for Chosen has a better performance than other.
The Energy Audit would give a positive orientation for implementing the energy cost
reduction, preventive maintenance and quality control programmes which are vital for production and
utility activities. Energy Audit is the translation of conservation ideas into realities, by lending
technically feasible solutions with economic and other organizational considerations within a specified
time frame. This thesis deals with the identification of nature of losses in industry that manufacturers
food products. The energy accounting with the use of measuring instruments like lux-meter, power and
harmonic analyzer etc. helps to record and analyze data of energy usage. With the help of this data,
energy wastage and losses are calculated and recommendations are given to reduce these losses and
improve savings. Lastly, to deal with the issues of power quality, power quality assessment is done at
PCC.
Battery Aware Dynamic Scheduling for Periodic Task GraphsNicolas Navet
V. Rao, N. Navet, G. Singhal, A. Kumar, G.S. Visweswaran, "Battery Aware Dynamic Scheduling for Periodic Task Graphs", Proc. of the 14th International Workshop on Parallel and Distributed Real-Time Systems (WPDRTS 2006), Island of Rhodes, Greece, April 25-26, 2006.
Episode 60 : Pinch Diagram and Heat Integration
The optimal allocation of mass and energy within a unit operation, process and/or site.
Optimal allocation can be based on economic, environmental or other important objectives.
SAJJAD KHUDHUR ABBAS
Ceo , Founder & Head of SHacademy
Chemical Engineering , Al-Muthanna University, Iraq
Oil & Gas Safety and Health Professional – OSHACADEMY
Trainer of Trainers (TOT) - Canadian Center of Human
Development
SimScale teams up with Greenlite, a provider of regulatory and building analysis services, to explore how cloud-based CFD software can be used by engineers and architects to quickly and accurately calculate wind pressure coefficients for projects in the built environment. Importing simulation files into IES and thermal modeling tools gives designers an extra advantage to evaluate ventilation and possible overheating.
comparative analysis of pid and narma l2 controllers for shell and tube heat...INFOGAIN PUBLICATION
The application of this paper firstly simplified mathematical model for heat exchanger process has been developed and used for the dynamic analysis and control design. A conventional PID controller and Advanced Artificial Neural Network NARMA L2 Controller for Shell and Tube heat exchanger is proposed to control the cold water outlet temperature and test the best efficiency of NARMA L2 and PID controller.The control problem formulated as outlet cold water temperature is controlled variable and the inlet hot water temperature is manipulated variable the minimum possible time irrespective of load and process disturbances.Simulation and verified the mathematical model of the controller has been done in MATLAB Simulink. From the simulation results the prime controller has been chosen by comparing the criteria of the response such as settling time, rise time, percentage of overshoot and steady state error.The Neural NetworkNARMA L2 controller is founded to give finest performance for Shell and Heat exchanger problem like temperature control. Later Need to compare Conventional PID and Advance Artificial Neural NetworkNARMA L2 Controller results which lead to decide which one is best for Chosen has a better performance than other.
The Energy Audit would give a positive orientation for implementing the energy cost
reduction, preventive maintenance and quality control programmes which are vital for production and
utility activities. Energy Audit is the translation of conservation ideas into realities, by lending
technically feasible solutions with economic and other organizational considerations within a specified
time frame. This thesis deals with the identification of nature of losses in industry that manufacturers
food products. The energy accounting with the use of measuring instruments like lux-meter, power and
harmonic analyzer etc. helps to record and analyze data of energy usage. With the help of this data,
energy wastage and losses are calculated and recommendations are given to reduce these losses and
improve savings. Lastly, to deal with the issues of power quality, power quality assessment is done at
PCC.
Battery Aware Dynamic Scheduling for Periodic Task GraphsNicolas Navet
V. Rao, N. Navet, G. Singhal, A. Kumar, G.S. Visweswaran, "Battery Aware Dynamic Scheduling for Periodic Task Graphs", Proc. of the 14th International Workshop on Parallel and Distributed Real-Time Systems (WPDRTS 2006), Island of Rhodes, Greece, April 25-26, 2006.
On May 26th, 2015, Monte Wilson of Jacobs Engineering Group and Mark Banta of Piedmont Park Conservancy presented to the board of directors of the Buckhead Community Improvement District a concept of capping the GA400 highway in the central core of Buckead to create a large park, similar to the Klyde Warren Park in Dallas.
Thermal aware task assignment for multicore processors using genetic algorithm IJECEIAES
Microprocessor power and thermal density are increasing exponentially. The reliability of the processor declined, cooling costs rose, and the processor's lifespan was shortened due to an overheated processor and poor thermal management like thermally unbalanced processors. Thus, the thermal management and balancing of multi-core processors are extremely crucial. This work mostly focuses on a compact temperature model of multicore processors. In this paper, a novel task assignment is proposed using a genetic algorithm to maintain the thermal balance of the cores, by considering the energy expended by each task that the core performs. And expecting the cores’ temperature using the hotspot simulator. The algorithm assigns tasks to the processors depending on the task parameters and current cores’ temperature in such a way that none of the tasks’ deadlines are lost for the earliest deadline first (EDF) scheduling algorithm. The mathematical model was derived, and the simulation results showed that the highest temperature difference between the cores is 8 C for approximately 14 seconds of simulation. These results validate the effectiveness of the proposed algorithm in managing the hotspot and reducing both temperature and energy consumption in multicore processors.
Heating & Cooling Loads Calculations and HVAC Equipment SizingIES VE
IESVE Software is a suite of integrated analysis tools for the design and optimisation of buildings. This 1-hour webinar focused on the loads-specific use cases.
Workload-Based Prediction of CPU Temperature and Usage for Small-Scale Distri...Tarik Reza Toha
The recent boost in the usage of high-performance computing systems in small research environments, such as those found at many universities, stipulates the need of smallscale distributed systems. Owning to the rapid growth in both computing power and heat, development of proper thermal and resource management becomes crucial concern of the research community along with the vendors to ensure efficiency for such systems. Moreover, an accurate and relatively fast strategy is needed for adaptation of different sizes of workload in such systems. Therefore, in this paper, we focus on developing simple prediction models of CPU temperature and usage for the systems. We investigate impacts of macro-level parameters such as the number of machines and different sizes of workload on CPU temperature and usage via real experiment. Our experimental results reveal that for a certain size of workload, the variation in CPU temperature and usage is minimal in response to a change in the number of machines, which does not hold in the reverse way. Hence, we develop workload-based prediction models for CPU temperature and usage. We evaluate the accuracy of our models by comparing the values calculated based on these models against the measurements found from real implementation.
This presentation is to show how to design heat exchanger from process simulation data to complete mechanical design by using two software HTRI and COMPRESS in seamless streamline Auto duping data.
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!
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
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
As AI technology is pushing into IT I was wondering myself, as an “infrastructure container kubernetes guy”, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefit’s both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
DevOps and Testing slides at DASA ConnectKari Kakkonen
My and Rik Marselis slides at 30.5.2024 DASA Connect conference. We discuss about what is testing, then what is agile testing and finally what is Testing in DevOps. Finally we had lovely workshop with the participants trying to find out different ways to think about quality and testing in different parts of the DevOps infinity loop.
Connector Corner: Automate dynamic content and events by pushing a buttonDianaGray10
Here is something new! In our next Connector Corner webinar, we will demonstrate how you can use a single workflow to:
Create a campaign using Mailchimp with merge tags/fields
Send an interactive Slack channel message (using buttons)
Have the message received by managers and peers along with a test email for review
But there’s more:
In a second workflow supporting the same use case, you’ll see:
Your campaign sent to target colleagues for approval
If the “Approve” button is clicked, a Jira/Zendesk ticket is created for the marketing design team
But—if the “Reject” button is pushed, colleagues will be alerted via Slack message
Join us to learn more about this new, human-in-the-loop capability, brought to you by Integration Service connectors.
And...
Speakers:
Akshay Agnihotri, Product Manager
Charlie Greenberg, Host
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.
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
Generating a custom Ruby SDK for your web service or Rails API using Smithyg2nightmarescribd
Have you ever wanted a Ruby client API to communicate with your web service? Smithy is a protocol-agnostic language for defining services and SDKs. Smithy Ruby is an implementation of Smithy that generates a Ruby SDK using a Smithy model. In this talk, we will explore Smithy and Smithy Ruby to learn how to generate custom feature-rich SDKs that can communicate with any web service, such as a Rails JSON API.
Dev Dives: Train smarter, not harder – active learning and UiPath LLMs for do...UiPathCommunity
💥 Speed, accuracy, and scaling – discover the superpowers of GenAI in action with UiPath Document Understanding and Communications Mining™:
See how to accelerate model training and optimize model performance with active learning
Learn about the latest enhancements to out-of-the-box document processing – with little to no training required
Get an exclusive demo of the new family of UiPath LLMs – GenAI models specialized for processing different types of documents and messages
This is a hands-on session specifically designed for automation developers and AI enthusiasts seeking to enhance their knowledge in leveraging the latest intelligent document processing capabilities offered by UiPath.
Speakers:
👨🏫 Andras Palfi, Senior Product Manager, UiPath
👩🏫 Lenka Dulovicova, Product Program Manager, UiPath
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.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
Key Trends Shaping the Future of Infrastructure.pdf
Final_project
1.
2. Abstract
0 The aggressive semiconductor technology scaling has been pushing the
device feature size into the deep sub-micron region.
0 As a result, the chip power density has been doubled every two to three
years.
0 This increased power has directly translated into high temperature,
which negatively affects a system's cost, performance and reliability.
0 In this review, various methodologies for thermal and energy problem
mitigation are presented and compared
3. Power Consumption Issues
0 Stress on batteries in portable devices such as laptops and phones
0 Can be minimized through voltage and frequency scaling
0 High temperature greatly shortens the lifespan of a processor
0 100C increase in temperature reduces component life by 50% [1]
0 Obvious approach is to use bigger heat sinks and air- cooling techniques (for desktop
and laptop computers)
0 Expensive and inefficient
0 Power- aware techniques are not efficient in handling these issues
0 Logic blocks within the chip have different power densities (e.g. due to
different levels of switching activity)
0 The thermal map of a chip often shows wide variations in temperature
0 Many low-power techniques have insufficient impact because they do not
directly target the spatial and temporal behavior of the operating
temperature.
4. Thermal- aware Computing [2]
0 Components of power consumption
0 Dynamic
0 consumed when devices switch from one logic level to another.
0 related to the level of computational (switching) activity
0 Leakage
0 power that flows from source to ground whenever a device is powered up
0 grows exponentially with temperature
0 Thermal modeling
0 Hotspot Heatflow model [3]
5. Thermal- aware Computing
0 Thermal- aware chip design (Static)
0 focus on the floorplanning phase of the physical design process [4,5,6,7]
0 Floorplanning algorithms can be modified to also include reducing the maximum
temperature of a block in the chip.
0 Migration Computing [8]
0 Increasing silicon area allocated to hotblocks [9]
0 Runtime Thermal Management (Dynamic)
0 The operating system controls the scheduling of tasks and also assign tasks to
individual cores
0
0
0
0
Heat Balancing
Heat Unbalancing
Reducing Execution Rate of Hot Tasks
Adding a Predictive Component
6. Thermal- aware Computing
Runtime Techniques
Methodology
Voltage Scaling
Change voltage levels to adjust power and
energy
consumption. Clock rates are reduced to match
the
increased circuit delay that results
Heat Balancing
Spreads the thermal load among multiple
cores to
approximately even out their temperatures.
Heat Unbalancing
Reduce thermal cycling effects: accept
significant
temperature differentials between the cores as
long as
specified temperature levels are not breached.
Throttling
Reduce the rate at which heat is generated by
reducing instruction fetch rate and similar
parameters.
7. Thermal- aware Scheduling
0 Thermal aware task allocation in SoCs
0 Dynamic Thermal Management through Task-Scheduling [18]
0 Thermal-Aware Task Allocation and Scheduling for Embedded Systems [19]
0 Static and Dynamic Temperature-Aware Scheduling for Multiprocessor SoCs
[20]
8. Thermal-Aware Task Allocation and Scheduling
for Embedded Systems (Hung et. al)
0 Proposed an algorithm that is used as a subroutine for
hardware/software co-synthesis
0 To exploit resource sharing
0 Traditional algorithms do not take the temperature and power variables
into consideration
0 Power awareness
0 Dynamic Criticality (DC)
0 Analogous to priority
0
9. Thermal-Aware Task Allocation and Scheduling
for Embedded Systems (Hung et. al)
0
The flows of the thermal-aware co-synthesis framework
and thermal-aware platform-based system design
0
The temperature comparisons of the power-aware and the
thermal-aware approaches on co-synthesis architecture.
10. Static and Dynamic Temperature-Aware Scheduling for
Multiprocessor SoCs (Coskun et. Al)
0 This looks at Multiprocessor SoCs
0 ILPs to generate static solutions
0 target thermal hotspots and gradients
0 better thermal profile than other static methods
0 Dynamic Scheduling (OS- level scheduling)
0 Adaptive –random technique
11. Static and Dynamic Temperature-Aware Scheduling for
Multiprocessor SoCs (Coskun et. Al)
12. Dynamic Thermal Management
through Task-Scheduling (Yang et. al)
0 ThreshHot Algorithm
0 reduces the number of hardware DTMs (Dynamic
thermal management) required.
0 Increase in CPU throughput
14. Comparative Table
Authors
Methodology
Static Thermal
Management
Dynamic
thermal
Management
Static Energy
Management
Dynamic
Energy
Management
Issues
Hung et. al
Implemented
algorithm with
temperature
and power
vaiables
No
Yes
No
Yes
Floorplanning is
not effective to
control the
lateral heat
transfer.
Overhead due to
dynamic nature
Coskun et. al
Implemented
adaptive –
random
scheduling
algorithm
Yes
Yes
No
Yes
Overhead
associated with
dynamic
awareness is
high
Yang et. al
Implemented
ThresHot
scheduling
algorithm
No
Yes
No
Yes
Overhead
associated with
dynamic
awareness is
high
15. Energy- aware Computing
0 Energy consumption is a critical measure for battery powered and
tethered devices.
0 Energy can be reduced by
0 Static
0 Dynamic
0 DVFS
0 Examples
0
0
0
0
0
idle functional units can be powered down [10]
clock gating [11]
low-power design [12]
low-power synthesis [13]
lower the operating voltage level during the design/synthesis phase [14]
17. Energy-Aware Task Allocation for Rate
Monotonic Scheduling (AlEnawy et. al)
0 adopt partitioned scheduling and assume that tasks are assigned static
(rate-monotonic) priorities.
0 study and evaluate a number of well-known partitioning heuristics,
RMS admission control algorithms, and speed assignment schemes in
terms of the feasibility performance and overall energy consumption.
0 Off-line and on-line partitioning
19. Real-time task scheduling for energy-aware
embedded systems (Swaminathan et. al)
0 Two on-line scheduling algorithms that attempt to
minimize the energy consumed by a periodic task set
0 Both using EDF
0 LEDF
0 E- LEDF
21. Energy-Aware Runtime Scheduling for Embedded
Multiprocessor SOCs (Yang et. al)
0 Preorder the concurrent behavior as much as possible
0 This task-scheduling method for embedded systems
combines the low runtime complexity of a designtime scheduling phase with the flexibility of a runtime
scheduling phase.
0 increases design flexibility and reduces design time
for multiprocessor SOCs
23. Comparative Table
Authors
Methodology
Static Energy
Management
Dynamic Energy
Management
Issues
AlEnawy et. al
Partitioned task
scheduling with
static priorities
Yes
Yes
Does not have good
performance for online partitioning and
overhead due to
dynamic computations
Swaminathan et. al
Implemented on-line
scheduling
algorithms based on
EDF
No
Yes
Difficulty with
Aperiodic and
sporadic tasks
and overhead due to
dynamic
computations
Yang et. al
Algorithm combines
the low runtime
complexity of a
design-time
scheduling phase
with the flexibility of
a runtime scheduling
phase.
No
Yes
Ineffective for very
heavy loads and
difficult to implement
for practical
applications
24. Conclusions
0 Thermal management techniques always outperform the
energy management techniques
0 Not every technique is easily implementable for practical
applications
0 Runtime techniques offer control at a fine level of
granularity, but have an overhead associated with them
0 A lot of research in this field of study